Merge branch 'main' of https://cau-git.rz.uni-kiel.de/nt/mitarbeiter/silas/imdd_simulation

.gitignore

@@ -21,3 +21,5 @@ sccprj/
 # Matlab code generation folders
 codegen/
 
+
+.mat

Classes/00_signals/Signal.m

@@ -359,10 +359,10 @@ classdef Signal
             end
             
             if options.normalizeToNyquist == 0
-                [p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,obj.fs,"centered","psd","mean");
+                [p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,obj.fs,"centered","power","mean");
                 w = w.*1e-9;
             else
-                [p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,"centered","psd","mean");
+                [p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,"centered","power","mean");
             end
 
             if options.normalizeTo0dB
@@ -411,8 +411,9 @@ classdef Signal
             try
             ylim([max(min(floor(min(p_dbm))-3, ax.YLim(1)),-40), min(max(ceil(max(p_dbm))+3, ax.YLim(2)),10)]);
             catch
-            ylim([min(floor(min(p_dbm))-3, ax.YLim(1)), max(ceil(max(p_dbm))+3, ax.YLim(2))]);
+            ylim([floor(min(p_dbm))-3, ceil(max(p_dbm))+3]);
             end
+            ylim([floor(min(p_dbm))-3, ceil(max(p_dbm))+3]);
             yticks(-200:10:10);
             grid on; grid minor;
             legend
@@ -655,14 +656,23 @@ classdef Signal
         end
 
         %%
-        function [obj,S,isFlipped] = tsynch(obj,options)
+        function [obj,S,isFlipped,sequenceFound] = tsynch(obj,options)
             % time sync and cut
             arguments
                 obj Signal
                 options.reference Signal
                 options.fs_ref = 0;
+                options.debug_plots = 0;
             end
      
+            
+            
+            S = {};
+            isFlipped=0;
+            sequenceFound = 0;
+
+
+
             %normalize the signal
             a = obj.normalize("mode","oneone").signal;
 
@@ -679,29 +689,46 @@ classdef Signal
 
             %estimate start pos of signal
             maxpeaknum = floor(length(a)/length(b));
-            [pks,pkpos] = findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend');
+            try
+                [pks,pkpos,w,p] = findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend');
+            catch
+                warning(['Error in findpeaks, ususally the seuqnece is too short. Max peak num: ', num2str(maxpeaknum)]);
+                return
+            end
+
+            if mean(w) > 10 || mean(p) > 10
+                return
+            else
+                sequenceFound = 1;
+            end
+
+            if options.debug_plots
+                figure()
+                findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend')
+            end
+
+            
+
             shifts = lags(pkpos);
 
             shifts = shifts(shifts>=0);
 
-            S = {};
-            isFlipped=0;
-
             if numel(shifts) > 0
     
                 %Cut occurences of ref signal from signal (only positive shifts)
+                if all(sign(co(pkpos)))
+                    isFlipped = 1;
+                end
                
                 for c = shifts(shifts>=0)
                     sig = obj.delay(-c,'mode','samples');
-                    sig.signal = sig.signal(1:length(b));
+                    sig.signal = sig.signal(1:length(b)).*-isFlipped;
                     S{end+1,1} = sig;
                 end
     
                 %
                 
-                if all(sign(co(pkpos)))
-                    isFlipped = 1;
-                end
+
     
                 %return/keep the sinal with the highest correlation (only within positive shifts)
                 [~,idx]=max(pks(shifts>=0));
@@ -722,8 +749,7 @@ classdef Signal
             end
 
             %plot all synced signals and the ref signal
-            debug = 0;
-            if debug
+            if options.debug_plots
                 figure;hold on;
                 for i = 1:size(S,1)
                     plot(S{i}.normalize('mode','oneone').signal(1000:1100),'LineWidth',0.1,'Color',[0.2157    0.4941    0.7216]);
@@ -735,6 +761,12 @@ classdef Signal
 
 
         end
+
+
+
+
+
+
         %%
         function obj = filter(obj,a,b)
 
@@ -850,7 +882,10 @@ classdef Signal
                 sig = obj.signal;
             end
 
-            x = (sig);                                               %% make input signal rea)l
+            startpos = floor(0.1*length(sig));
+            endpos = floor(0.9*length(sig));
+            endpos = min(endpos,startpos+200000);
+            x = sig(startpos:endpos);                                               %% make input signal rea)l
 
             x = resample(x,fsym*histpoints_horizontal/2,obj.fs);         %% up sample to original fsym rate
 

Classes/01_transmit/ChannelFreqResp.m

@@ -241,10 +241,13 @@ classdef ChannelFreqResp < handle
             xlim([0.2 .5*max(obj.faxis)*1e-9]); grid on;
 
             %%% plot for publication
-            figure(1234);hold all;box on;title('Magnitude Freq. Response');
-            %xlim([0.2 .5*max(obj.faxis)*1e-9]);
-            %ylim([-40, 2]);
-            Havg_smooth = smooth(Havg,50);
+            figure(1234);
+            hold all;
+            box on;
+            title('Magnitude Freq. Response');
+            xlim([0.2 .5*max(obj.faxis)*1e-9]);
+            ylim([-40, 2]);
+            % Havg_smooth = smooth(Havg,10);
             symaxis = (obj.faxis-(obj.f_ref/2))/1e9; 
             Havg = fftshift(Havg);
             %Havg = smooth(Havg);

Classes/01_transmit/PAMmapper.m

@@ -8,13 +8,21 @@ classdef PAMmapper
         thresholds
         levels
         scaling
+        eth_style
     end
 
     methods
-        function obj = PAMmapper(M, unipolar)
+        function obj = PAMmapper(M, unipolar, options)
             %PAMMAPPER Construct an instance of this class
             %   Detailed explanation goes here
+            arguments
+                M
+                unipolar
+                options.eth_style = 0;
+            end
+
             obj.M = M;
+
             obj.unipolar = unipolar;
 
             obj.thresholds = obj.get_demodulation_thresholds();
@@ -23,6 +31,8 @@ classdef PAMmapper
 
             obj.scaling = rms(obj.get_levels());
 
+            obj.eth_style = options.eth_style;
+
         end
 
         function out = map(obj,signal_in)
@@ -44,9 +54,9 @@ classdef PAMmapper
             issignalclass = 0;
 
             if isa(signal_in,'Signal')
-               signalclass = signal_in;
-               signal_in = signal_in.signal;
-               issignalclass = 1;
+                signalclass = signal_in;
+                signal_in = signal_in.signal;
+                issignalclass = 1;
             end
 
             signal_out = obj.demap_(signal_in);
@@ -66,46 +76,110 @@ classdef PAMmapper
             switch obj.M
                 case 2
                     % 2-ASK: BPSK / OOK
-                    pam_sig=bitpattern(:,1);
-
-                    if obj.unipolar==0
-                        pam_sig=2*pam_sig-1;
+                    if ~obj.eth_style
+                        pam_sig = bitpattern(:,1);
+                        if obj.unipolar==0
+                            pam_sig=2*pam_sig-1;
+                        end
+                    else
+                        pam_sig = -2*bitpattern(:,1) + 1;
                     end
 
                 case 4
                     % 4-ASK:
-                    pam_sig=2*bitpattern(:,1)+(bitpattern(:,1)==bitpattern(:,2));
+                    if ~obj.eth_style
+                        pam_sig=2*bitpattern(:,1)+(bitpattern(:,1)==bitpattern(:,2));
 
-                    if obj.unipolar==0
-                        pam_sig=2*pam_sig-3;
+                        if obj.unipolar==0
+                            pam_sig=2*pam_sig-3;
+                        end
+                    else
+                        pam_sig = (2*bitpattern(:,1)-1).*(-2*bitpattern(:,2)+3);
                     end
 
                     pam_sig = pam_sig/sqrt(5);
 
                 case 6
 
-                    m = 1;
-                    if size(bitpattern,2)>size(bitpattern,1)
-                        bitpattern = bitpattern'; %vector aufrecht stellen
-                    end
-                    % LUT based mapping
-                    for k = 1:5:fix(length(bitpattern)/5)*5
-                        pam_sig(m:m+1,1) = obj.thresholds(bin2dec(int2str(bitpattern(k:k+4)'))+1,:);
-                        m = m+2;
+                    if ~obj.eth_style
+
+                        m = 1;
+                        if size(bitpattern,2)>size(bitpattern,1)
+                            bitpattern = bitpattern'; %vector aufrecht stellen
+                        end
+
+                        % LUT based mapping
+                        for k = 1:5:fix(length(bitpattern)/5)*5
+                            pam_sig(m:m+1,1) = obj.thresholds(bin2dec(int2str(bitpattern(k:k+4)'))+1,:);
+                            m = m+2;
+                        end
+
+                    else
+
+                        bitsPerSymbol = reshape(bitpattern,5,[]).'; % reorder 5 bits per symbol
+                        normFactor = 1;
+                        %====================32 QAM===================%
+                        %=============================================%
+                        %                  Coding                     %
+                        %         01000  01001 |11001  11000          %
+                        %                      |                      %
+                        %  01010  01110  01100 |11100  11110  11010   %
+                        %                      |                      %
+                        %  01011  01111  01101 |11101  11111  11011   %
+                        %  --------------------|-------------------   %
+                        %  00011  00111  00101 |10101  10111  10011   %
+                        %                      |                      %
+                        %  00010  00110  00100 |10100  10110  10010   %
+                        %                      |                      %
+                        %         00000  00001 |10001  10000          %
+                        %=============================================%
+                        % modulate three LSB first in first Quadrant
+                        % first bit inverts real part if 0
+                        % second bit inverts imaginary part if 0
+
+                        LSB_symbols = normFactor*(...
+                            +(1+1i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==1)...
+                            +(3+1i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==1)...
+                            +(5+1i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==1)...
+                            +(1+3i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==0)...
+                            +(3+3i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==0)...
+                            +(5+3i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==0)...
+                            +(1+5i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==1)...
+                            +(3+5i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==0));
+
+                        Re = real(LSB_symbols);
+                        Im = imag(LSB_symbols);
+                        % if first bit== 0  => invert real part
+                        % if second bit== 0 => invert imag part
+                        modData2 = Re.*(bitsPerSymbol(:,1)*2-1) + 1i*Im.*(bitsPerSymbol(:,2)*2-1);
+                        Re = real(modData2(1:end/2));
+                        Im = imag(modData2(1:end/2));
+                        pam_sig = zeros(length(Re)*2,1);
+                        pam_sig(1:2:length(Re)*2) = Re;
+                        pam_sig(2:2:length(Im)*2) = Im;
+
+
                     end
 
                     pam_sig = pam_sig/sqrt(10);
 
                 case 8
+
                     % 8-ASK:
-                    x1 = bitpattern(:,1);
-                    x2 = (bitpattern(:,1)==bitpattern(:,3));
-                    x3 = x2~=bitpattern(:,2);
+                    if ~obj.eth_style
+                        x1 = bitpattern(:,1);
+                        x2 = (bitpattern(:,1)==bitpattern(:,3));
+                        x3 = x2~=bitpattern(:,2);
 
-                    pam_sig = 4*x1 + 2*x2 + x3;
+                        pam_sig = 4*x1 + 2*x2 + x3;
+
+                        if obj.unipolar==0
+                            pam_sig=2*pam_sig-7;
+                        end
+                    else
+
+                        pam_sig = (bitpattern(:,1)*2-1).*(4+(2*bitpattern(:,2)-1).*(-2*bitpattern(:,3)+3));
 
-                    if obj.unipolar==0
-                        pam_sig=2*pam_sig-7;
                     end
 
                     pam_sig = pam_sig/sqrt(21);
@@ -210,7 +284,9 @@ classdef PAMmapper
         end
 
         function [data_out] = demap_(obj,data_in)
+            
             data_in= data_in';
+
             if obj.M ~= 6
 
                 % create output
@@ -227,48 +303,96 @@ classdef PAMmapper
 
                 s1=size(comp_real,1);
                 s2=size(comp_real,2);
+
             end
 
             switch obj.M
 
                 case 2
                     % 2-ASK
-
-                    data_out=comp_real(:,:,1);
+                    if ~obj.eth_style
+                        data_out=comp_real(:,:,1);
+                    else
+                        data_out=abs(comp_real(:,:,1)-1);
+                    end
 
                 case 4
                     % 4-ASK
-
-                    data_out=[comp_real(:,:,2); ones(s1,s2) - comp_real(:,:,1) + comp_real(:,:,3)];
+                    if ~obj.eth_style
+                        data_out=[comp_real(:,:,2); ones(s1,s2) - comp_real(:,:,1) + comp_real(:,:,3)];
+                    else
+                        data_out= [(data_in>=0); (abs(data_in)<=1)];
+                    end
 
                 case 6
 
-                    data_in = data_in/(sqrt(mean(abs(data_in).^2)));
-                    data_in = data_in*sqrt(10);
+                    if ~obj.eth_style
+
+                        data_in = data_in/(sqrt(mean(abs(data_in).^2)));
+                        data_in = data_in*sqrt(10);
+
+                        if size(data_in,2) > 1
+                            data_in = data_in.';
+                        end
+
+                        if length(data_in)/2 ~= round(length(data_in)/2)
+                            data_in = [data_in;0];
+                        end
+
+                        m = 1;
+                        for n = 1:2:length(data_in)
+                            dist = sqrt((data_in(n)-obj.thresholds(:,1)).^2+(data_in(n+1)-obj.thresholds(:,2)).^2);
+                            [~,dd_idx] = min(dist);
+                            %                 dec_out(n:n+1) = LUT(dd_idx,:);
+                            data_out(m:m+4) = bitget(dd_idx-1,5:-1:1);
+                            m = m+5;
+                        end
+                        
+                    else
+                        
+                        data_in= data_in';
+                        rxSym = data_in(1:2:end) + 1i*data_in(2:2:end);  % 16×1
+
+                        % Decode the sign bits (bits 1 & 2).
+                        rxBit1 = double(real(rxSym) > 0);
+                        rxBit2 = double(imag(rxSym) > 0);
+
+                        % Undo the quadrant inversion and normalization.
+                        rxSym_corr = abs(real(rxSym)) + 1i*abs(imag(rxSym));
+                        normFactor = 1/sqrt(10);
+                        rxSym_unscaled = rxSym_corr / normFactor;
+
+
+                        cand = [1+1i, 3+1i, 5+1i, 1+3i, 3+3i, 5+3i, 1+5i, 3+5i];
+                        candBits = [1 0 1;
+                            1 1 1;
+                            0 1 1;
+                            1 0 0;
+                            1 1 0;
+                            0 1 0;
+                            0 0 1;
+                            0 0 0];
+                        d = abs(rxSym_unscaled - cand).^2;  % 32×8 distances
+                        [~, idx] = min(d, [], 2);
+                        rxLSB = candBits(idx,:);  % 32×3
+
+
+                        decodedSymbols = [rxBit1, rxBit2, rxLSB];
+                        data_out = reshape(decodedSymbols.', [], 1).';
 
-                    if size(data_in,2) > 1
-                        data_in = data_in.';
                     end
 
-                    if length(data_in)/2 ~= round(length(data_in)/2)
-                        data_in = [data_in;0];
-                    end
-        
-                    m = 1;
-                    for n = 1:2:length(data_in)
-                        dist = sqrt((data_in(n)-obj.thresholds(:,1)).^2+(data_in(n+1)-obj.thresholds(:,2)).^2);
-                        [~,dd_idx] = min(dist);
-        %                 dec_out(n:n+1) = LUT(dd_idx,:);
-                        data_out(m:m+4) = bitget(dd_idx-1,5:-1:1);
-                        m = m+5;
-                    end
 
 
                 case 8
                     % 8-ASK
-                    data_out=[comp_real(:,:,4);
-                        comp_real(:,:,1)-comp_real(:,:,3)+comp_real(:,:,5)-comp_real(:,:,7);
-                        1-comp_real(:,:,2)+comp_real(:,:,6)];
+                    if ~obj.eth_style
+                        data_out=[comp_real(:,:,4);
+                            comp_real(:,:,1)-comp_real(:,:,3)+comp_real(:,:,5)-comp_real(:,:,7);
+                            1-comp_real(:,:,2)+comp_real(:,:,6)];
+                    else
+                        data_out = [(data_in>=0); (abs(data_in)>(4/sqrt(21))); (abs(data_in)>=(2/sqrt(21)))&(abs(data_in)<=(6/sqrt(21)))];
+                    end
 
                 case 16
                     % 16-ASK
@@ -355,6 +479,10 @@ classdef PAMmapper
 
         end
 
+        function bitmap = showBitMapping(obj)
+            bitmap = obj.demap([obj.levels ./ obj.scaling]');
+        end
+
     end
 
 end

Classes/01_transmit/PAMsource.m

@@ -71,18 +71,17 @@ classdef PAMsource
         function  [digi_sig,symbols,bits] = process(obj)
 
             %%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
-            O = obj.order; %order of prbs
-            N = 2^(O-1); %length of prbs
-            [~,seed] = prbs(O,1); %initialize first seed of prbs
             bitpattern=[];
 
             if obj.useprbs
-                % for i = 1:log2(obj.M)
-                %     [bitpattern(:,i),seed] = prbs(O,N,seed);
-                % end
+                %     O = obj.order; %order of prbs
+                %     N = 2^(O-1); %length of prbs
+                %     [~,seed] = prbs(O,1); %initialize first seed of prbs
+                %     % for i = 1:log2(obj.M)
+                %     %     [bitpattern(:,i),seed] = prbs(O,N,seed);
+                %     % end
 
                 %%%%% MOVE-IT PRMS %%%%
-
                 state = struct();
 
                 para = struct();
@@ -103,6 +102,8 @@ classdef PAMsource
                 para.reset_prms = 0;
                 para.method = 1;
 
+                
+
                 data_in = [];
                 global loop;
                 loop = 0;
@@ -116,6 +117,7 @@ classdef PAMsource
             else
                 s = RandStream('twister','Seed',obj.randkey);
                 for i = 1:log2(obj.M)
+                    N = 2^(obj.order-1); %length of prbs
                     bitpattern(:,i) = randi(s,[0 1], N, 1);
                 end
             end
@@ -151,23 +153,52 @@ classdef PAMsource
                 sym_max = max(symbols.signal);
             end
 
-            % symbols.move_it_spectrum("fignum",222,"displayname","Symbols only");
-
-
-            % symbols.spectrum("fignum",222,"displayname","Symbols only","normalizeTo0dB",1);
 
 
             %%%%% Pulse-forming %%%%%%
             if obj.applypulseform
+                %%% MY CODE
                 digi_sig = obj.pulseformer.process(symbols);
+
+                %%% MOVEIT WRAPPER BETA
+                % symbols.spectrum("fignum",111,"displayname","1) RAW SIGNAL");
+                % 
+                % pulsf = Moveit_wrapper('pulsef');
+                % pulsf.para.alpharacos = obj.pulseformer.alpha;
+                % pulsf.para.f_sym = obj.fsym;
+                % pulsf.para.fs = obj.fsym;
+                % pulsf.para.pulse = 2;
+                %
+                % digi_sig = pulsf.process(symbols);
+
+                % Design raised cosine filter with given order in symbols
+                % digi_sig = symbols;
+                % sps = 4;
+                % nsym = 128;
+                % rctFilt3 = comm.RaisedCosineTransmitFilter(...
+                %     Shape='Square root', ...
+                %     RolloffFactor=1, ...
+                %     FilterSpanInSymbols=nsym, ...
+                %     OutputSamplesPerSymbol=sps);
+                % 
+                % digi_sig.signal = rctFilt3([symbols.signal; zeros(nsym/2,1)]);
+                % % Correct for propagation delay by removing filter transients
+                % fltDelay = nsym / (2*obj.fsym);
+                % digi_sig.signal = digi_sig.signal(fltDelay*sps*obj.fsym+1:end);
+                % 
+                % digi_sig.fs = sps .* symbols.fs;
+
+
             else
                 digi_sig = symbols;
             end
 
-            %%%%% Re-sample to f DAC %%%%%%
-            digi_sig = digi_sig.resample("fs_in",digi_sig.fs,"fs_out",obj.fs_out,"n",10,"beta",5);
 
-            %  digi_sig.spectrum("fignum",111,"displayname","after pulseforming");
+            %%%%% Re-sample to f DAC %%%%%%
+            n = 10;
+            digi_sig = digi_sig.resample("fs_in",digi_sig.fs,"fs_out",obj.fs_out,"n",n,"beta",5);
+            % digi_sig.spectrum("fignum",111,"displayname",['3) Shaped + Resampled; n: ',num2str(n)]);
+
 
             %%%%% Hard clip digital signal to PAM range before DAC %%%%%%
             if obj.applyclipping

Classes/01_transmit/Pulseformer.m

@@ -3,13 +3,17 @@ classdef Pulseformer
     %   Detailed explanation goes here
 
     properties(Access=public)
-        fdac
+        
     end
-    properties(Access=private)
+    properties(Access=public)
+        fs
         fsym
+        matched_sps
+        output_sps
         pulse
         pulselength
-        rrcalpha
+        alpha
+        matched
     end
 
     methods (Access=public)
@@ -18,11 +22,14 @@ classdef Pulseformer
             %   Detailed explanation goes here
 
             arguments
-                options.fdac double 
+                options.fs double 
                 options.fsym double 
-                options.pulse pulseform = pulseform.rrc
+                options.matched_sps double
+                options.output_sps double
+                options.pulse pulseform = pulseform.rc
                 options.pulselength double {mustBeInteger} = 32
-                options.rrcalpha double = 0.05
+                options.alpha double = 0.05
+                options.matched = 0;
             end
 
             %
@@ -47,7 +54,11 @@ classdef Pulseformer
             signalclass_in  = signalclass_in.logbookentry(lbdesc);
 
             % write fs to signal 
-            signalclass_in.fs = obj.fdac;
+            if obj.matched
+                signalclass_in.fs = obj.fsym .* obj.output_sps;%.* (obj.fdac./obj.fsym);
+            else
+                signalclass_in.fs = obj.fs;%.* (obj.fdac./obj.fsym);
+            end
 
             % write to output
             signalclass_out = signalclass_in;
@@ -74,60 +85,99 @@ classdef Pulseformer
                 data_out 
             end
 
-            if ~rem(obj.fdac,obj.fsym)
+            if ~isempty(obj.output_sps)
+                obj.fsym = obj.fsym.*obj.output_sps;
+            end
+
+            if ~rem(obj.fs,obj.fsym)
                 %ist ein Vielfaches
-                sps = obj.fdac / obj.fsym;
-                up = sps;
-                dn = 1;
+                sps = obj.fs / obj.fsym;
+                p = sps;
+                q = 1;
             else
                 %ist kein Vielfaches
-                up = obj.fdac / gcd(obj.fdac, obj.fsym);
-                dn = obj.fsym / gcd(obj.fdac, obj.fsym);
-                sps= up;
+                p = obj.fsym  / gcd(obj.fs, obj.fsym); %upsampling    p->->->
+                q = obj.fs/ gcd(obj.fs, obj.fsym); %downsampling     <-q
+                sps= q; %sps während dem pulse shaping 
             end
 
-            if obj.pulse ==  pulseform.rrc
-                %Bau das Filter (hier rrc)
-                racos_len   = obj.pulselength*2;
-                alpha       = obj.rrcalpha;
-                h           = rcosdesign(alpha,racos_len,sps,"normal");
-                h           = h./ max(h);
+            if obj.pulse ==  pulseform.rc
+                filtertype = 'normal';
+            elseif  pulseform.rrc
+                filtertype = 'sqrt';
             end
 
-            % Apply filter the long way (from move_it)
-            % block length in samples 
+            %Bau das Filter (hier rc)
+            racos_len   = obj.pulselength*2;
+            h           = rcosdesign(obj.alpha,racos_len,sps,filtertype);
+            % h           = h./ max(h);
 
-            data_in = data_in';
-            blen = length(data_in)*sps;
-        
-            % oversample symbol sequence
-        
-            symbolov=zeros(size(data_in,1),blen);
-            symbolov(:,1:sps:blen-sps+1)=data_in;
-
-            H=fft(h,blen);
-        
-            % Convolution of Bit sequence with impulse response
-
-            % cyclic convolution         
-            data_out=ifft( fft(symbolov.') .* repmat( H,size(data_in,1),1 ).' ).';
-
-            data_out = circshift(data_out,[0 -(obj.pulselength*sps)]);
-
-            if rem(obj.fdac,obj.fsym)
-                data_out = data_out(1:dn:end); %!
+            if obj.matched 
+                h  = conj(fliplr(h));
             end
             
+            manual_cyclic_convolution = 0;
+            upsample_filter = 0;
+            upfirdn_convolution = 1;
 
-%             %Apply Filter using Matlab build in fctn.
-%              h           = rcosdesign(alpha,racos_len,sps);
-%              h           = h./ max(h);
-             %data_out_ = upfirdn(data_in,h,up,dn);
-% 
-%             %cut signal, which is longer due to fir filter
-            %  st = round(up/dn*racos_len/2); %we need to cut y_out
-            % en = round(st + (length(data_in)*up/dn) -1);
-            % data_out = data_out(st:en);
+            if manual_cyclic_convolution
+
+                % Apply filter the long way (from move_it)
+                data_in = data_in';
+                blen = length(data_in)*sps;
+            
+                % oversample symbol sequence
+                symbolov=zeros(size(data_in,1),blen);
+                symbolov(:,1:sps:blen-sps+1)=data_in;
+                H=fft(h,blen);
+            
+                % Convolution of Bit sequence with impulse response
+                data_out=ifft( fft(symbolov.') .* repmat( H,size(data_in,1),1 ).' ).';
+                data_out = circshift(data_out,[0 -(obj.pulselength*sps)]);
+    
+                if rem(obj.fs,obj.fsym)
+                    data_out = data_out(1:q:end);
+                end
+
+            end
+
+            if upsample_filter
+                data_out_ = upsample(data_in,p);
+
+                mfOutput = filter(h, 1, data_out_); % Matched filter output
+
+                figure()
+                hold on
+                stem(mfOutput(1:1000),'Marker','o','MarkerSize',1,'LineStyle','-','LineWidth',1);
+                stem(data_out_(1:1000),'Marker','o','MarkerSize',1,'LineStyle','-','LineWidth',1);
+
+
+            end
+
+            if upfirdn_convolution 
+
+               %Apply Filter using Matlab build in fctn.
+                data_out_   = upfirdn(data_in,h,p,q);
+
+                %cut signal, which is longer due to fir filter
+                st = round(p/q*racos_len/2); %we need to cut y_out
+                en = round(st + (length(data_in)*p/q));
+                data_out = data_out_(st:en);
+
+            end
+
+            if upfirdn_convolution && manual_cyclic_convolution
+                figure()
+                subplot(2,1,1)
+                title("Convolution vs. Upfirdn and Cut")
+                hold on
+                % plot(data_out_(1:200),'DisplayName','Matlab upfirdn');
+                plot(data_out(1:200),'DisplayName','By Hand cyclic convolution')
+                subplot(2,1,2)
+                hold on
+                plot(data_out(1:2000),'DisplayName','OUT');
+                plot(data_in(1:2000),'DisplayName','IN');
+            end
 
             %scaling?! see pulsef module line 696
 %             scale = max(max([abs(real(data_out)) abs(imag(data_out))])); %find max value from real and imag part
@@ -136,7 +186,7 @@ classdef Pulseformer
             data_out = data_out';
 
             %Check output integrity
-            if abs(round(up/dn * length(data_in)) - length(data_out)) > 4
+            if abs(round(p/q * length(data_in)) - length(data_out)) > 4
                 warning('Check signal length after pulse shaping');
                 %disp('Check signal length after pulse shaping');
             end

Classes/04_DSP/Coding/Duobinary.m

@@ -26,7 +26,9 @@ classdef Duobinary
             M = numel(u);
 
             %make unipolar
-            if M == 4
+            if M == 2
+                data = data;
+            elseif M == 4
                 data = data .* sqrt(5);
             elseif M == 6
                 data = data .* sqrt(10);
@@ -59,7 +61,9 @@ classdef Duobinary
             bk = bk .* 2;
             bk = bk + b;
 
-            if M == 4
+            if M == 2
+                bk = bk;
+            elseif M == 4
                 bk = bk ./ sqrt(5);
             elseif M == 6
                 bk = bk ./ sqrt(10);
@@ -100,7 +104,9 @@ classdef Duobinary
             end
 
             %make unipolar
-            if options.M == 4
+            if options.M == 2
+                data = data;
+            elseif options.M == 4
                 data = data .* sqrt(5);
             elseif options.M == 6
                 data = data .* sqrt(10);
@@ -140,7 +146,9 @@ classdef Duobinary
             mean_power = sum((unique_points .^ 2) .* probabilities);
             scaling_factor = sqrt(mean_power);
 
-            if options.M == 4
+            if options.M == 2
+                data = data ./ sqrt(0.5);
+            elseif options.M == 4
                 data = data ./ sqrt(2.5); % 7-level constellation weighted with probability after DB code i.e. mean([-3 3 -2 -2 2 2 -1 -1 -1 1 1 1 0 0 0 0].^2) = 2.5 --> sqrt(2.5) == rms(constellation)
             elseif options.M == 6
                 data = data ./ sqrt(5.8);
@@ -186,7 +194,9 @@ classdef Duobinary
             end
 
             %make unipolar
-            if I == 7 || I == 6
+            if I == 3
+                data = data .* 0.5;
+            elseif I == 7 || I == 6
                 data = data .* sqrt(2.5);
             elseif I == 11
                 data = data .* sqrt(5.8);
@@ -206,7 +216,9 @@ classdef Duobinary
             data = data .* 2;
             data = data - round(mean(data));
 
-            if M == 4
+            if M == 2
+                data = data;
+            elseif M == 4
                 data = data ./ sqrt(5);
             elseif M == 6
                 data = data ./ sqrt(10);

Classes/04_DSP/Equalizer/FFE.m

@@ -102,6 +102,17 @@ classdef FFE < handle
 
             x = [zeros(floor(obj.order/2),1); x; zeros(obj.order,1)];
 
+            if training
+                mask = ones(obj.order,1);
+            else
+                mask = zeros(obj.order,1);
+                mask(900:end) = 1;
+                mask(ceil(length(obj.e)/2)) = 1;
+            end
+
+            mask = ones(obj.order,1);
+
+            
             for epoch = 1 : epochs
                 symbol = 0;
                 for sample = 1 : obj.sps : N
@@ -110,7 +121,7 @@ classdef FFE < handle
 
                     U = x(obj.order+sample-1:-1:sample);
 
-                    y(symbol,1) = obj.e.' * U;    % Calculating output of LMS  __ * |
+                    y(symbol,1) = (obj.e.*mask).' * U;    % Calculating output of LMS  __ * |
 
                     if training
                         d_hat(symbol,1) = d(symbol);  
@@ -130,7 +141,6 @@ classdef FFE < handle
                         obj.e = obj.e - err(symbol) * U / normalizationfactor;    % Weight update rule of NLMS
                     end
 
-
                     obj.error(epoch,symbol) = err(symbol) * err(symbol)';  % Instantaneous square error
 
                 end

Classes/04_DSP/Equalizer/Postfilter.m

@@ -43,12 +43,12 @@ classdef Postfilter < handle
 
             if ~isnan(options.useBurg) && options.useBurg
                 
-                disp('using burg alg')
+                % disp('using burg alg')
                 obj.coefficients = arburg(noiseclass_in.signal,obj.ncoeff);
 
             elseif ~isempty(options.coefficients)
 
-                disp('using given taps')
+                % disp('using given taps')
                 obj.coefficients = options.coefficients;
                 obj.useBurg = 0;
 
@@ -67,22 +67,29 @@ classdef Postfilter < handle
 
         end
 
-        function showFilter(obj,noiseclass_in,options)
+        function showFilter(obj,options)
 
             arguments
                 obj 
-                noiseclass_in 
+                options.noiseclass_in =[]
                 options.fignum = 121
                 options.color = []
             end
 
             % noiseclass_in.spectrum('displayname','Noise PSD shifted to 0dBm','fignum',options.fignum,'normalizeTo0dB',1);
+            if ~isempty(options.noiseclass_in)
+            len = length(options.noiseclass_in);
+            fs = options.noiseclass_in.fs;
+            else
+                len = 1024;
+                fs = 1;
+            end
 
             figure(options.fignum)
-            [h,w] = freqz(1,obj.coefficients,length(noiseclass_in),"whole",noiseclass_in.fs);
+            [h,w] = freqz(1,obj.coefficients,len,"whole",fs);
             h = h/max(abs(h));
             hold on
-            w_ = (w - noiseclass_in.fs/2);
+            w_ = (w - fs/2);
             
             if isempty(options.color)
                 plot(w_.*1e-9,20*log10(fftshift(abs(h))),'DisplayName',['Burg Coeffs: ', num2str(round(obj.coefficients,2)), ' '],'LineWidth',2);

Classes/04_DSP/Sequence Detection/MLSE.m

@@ -70,7 +70,7 @@ classdef MLSE < handle
             %%%% Separate the equalized signal into the respective levels based on the actually transmitted level
             constellation    = unique(data_ref);
             decisionLevels   = (constellation(1:end-1) + constellation(2:end)) / 2;
-            tx_bits = PAMmapper(numel(constellation),0).demap(data_ref);
+            tx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(data_ref);
 
 
             % impulse respnse i.e. [0.5, 1.0000]
@@ -188,10 +188,50 @@ classdef MLSE < handle
                 
             end
 
+            % Compute soft output PAM4 stream from the metric_sym
+            soft_output = zeros(length(data_in),1);      % Expected symbol value per stage
+            symbol_prob = zeros(length(data_in), length(states)); % Store full probability distribution (optional)
+            llp = llp';
+            for n = 1:length(data_in)
+                metrics = llp(n, :);   % A posteriori metric for each PAM4 candidate
+                % For numerical stability, subtract the maximum metric before exponentiating
+                maxMetric = min(metrics);
+                expMetrics = exp(metrics - maxMetric);
+                probs = expMetrics / sum(expMetrics);  % Normalize to get probabilities
+                symbol_prob(n, :) = probs;              % (Optional) store distribution for analysis
+                % Compute the soft output as the expected value of the PAM4 symbols
+                soft_output(n) = sum(probs .* constellation');
+            end
+
+            % Number of symbols and bits per symbol
+            num_symbols = constellation;
+            num_bits = 2; % 2 bits per symbol
+
+            bit_mapping = PAMmapper(4,0,"eth_style",1).showBitMapping; % Each row corresponds to the symbol above
+
+            % Initialize LLR storage
+            llr = zeros(num_bits, length(data_in));
+
+            % Compute bit-wise LLRs
+            for bit_idx = 1:num_bits
+                % Find indices where bit is 0 and where it is 1
+                idx_bit_0 = find(bit_mapping(:,bit_idx) == 0);
+                idx_bit_1 = find(bit_mapping(:,bit_idx) == 1);
+
+                % Sum over log-probabilities (Max-Log approximation: using min instead of sum)
+                llr(:,bit_idx) = min(llp(:,idx_bit_1), [], 1) - min(llp(:,idx_bit_0), [], 1);
+               
+            end
+
+            % Convert LLR values to a hard-decision bit stream
+            bit_stream = llr < 0;
+            [~,~,ber_llr,~] = calc_ber(bit_stream',tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+            fprintf('LLR BER   : %.2e \n',ber_llr);
+
             % directly decide based on lowest LLP index
             [~,llp_based_state_seq]=min(llp);
             LLP_EST(1:length(data_in)) = constellation(llp_based_state_seq);
-            rx_bits = PAMmapper(numel(constellation),0).demap(LLP_EST');
+            rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(LLP_EST');
             [~,~,ber_llp,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             fprintf('LLP BER   : %.2e \n',ber_llp);
             % [~,~,ber_llp,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -200,7 +240,7 @@ classdef MLSE < handle
             % fprintf('LLP BER -1: %.2e \n',ber_llp);
             
             %%%% DECIDE based on Viterbi traceback
-            rx_bits = PAMmapper(numel(constellation),0).demap(VITERBI_ESTIMATION_SYMBOLS');
+            rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(VITERBI_ESTIMATION_SYMBOLS');
             [~,~,ber_viterbi,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             fprintf('Viterbi BER: %.2e \n',ber_viterbi);
             % [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -209,14 +249,14 @@ classdef MLSE < handle
             % directly decide based on the FW path metrics
             [~,fw_direct_state_seq]=min(pm_survivor_fw);
             FW_EST(1:length(data_in)) = constellation(fw_direct_state_seq);
-            rx_bits = PAMmapper(numel(constellation),0).demap(FW_EST');
+            rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(FW_EST');
             [~,~,ber_fw,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             fprintf('FW BER: %.2e \n',ber_fw);
 
             % directly decide based on the BW path metrics
             [~,bw_direct_state_seq]=min(pm_survivor_bw);
             BW_EST(1:length(data_in)) = constellation(bw_direct_state_seq(2:end));
-            rx_bits = PAMmapper(numel(constellation),0).demap(BW_EST');
+            rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(BW_EST');
             [~,~,ber_bw,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             fprintf('BW BER: %.2e \n',ber_bw);
             % [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -224,6 +264,8 @@ classdef MLSE < handle
             % [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,-1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             % fprintf('BW BER: %.2e \n',ber_viterbi);
 
+            PAMmapper(4,0,"eth_style",1).showBitMapping
+
 
             %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
             tx_symbolpos     = zeros(numel(constellation),length(data_ref));

Classes/04_DSP/TransmissionPerformance.m

@@ -59,9 +59,20 @@ classdef TransmissionPerformance
                             1.03e-2, 9.29e-3, 8.33e-3, 7.54e-3, 7.04e-3, 4.70e-3];
 
         %% LUT for KP4-FEC and Inner Code https://grouper.ieee.org/groups/802/3/dj/public/23_03/patra_3dj_01b_2303.pdf
+        
         CODE_RATE_KP4_AND_INNER = [0.885799];
         BERTHRESHOLDS_KP4_AND_INNER = 4.85e-3; 
 
+        % https://www.ieee802.org/3/bs/public/14_11/parthasarathy_3bs_01a_1114.pdf
+        CODE_RATE_KP4 = [1/(1+0.052)];%Reed-Solomon RS(544, 514) == KP4
+        BERTHRESHOLDS_KP4 = 2.2e-4; 
+
+        CODE_RATE_HDFEC = [1/(1+0.067)];  %Beyond 300 Gbps Short-Reach Links Using TFLN MZMs With 500 mVpp and Linear Equalization
+        BERTHRESHOLDS_HDFEC = 3.8e-3; 
+
+        CODE_RATE_O_FEC = [1/(1+0.153)]; %Stefano im Meeting
+        BERTHRESHOLDS_O_FEC = 2e-2; 
+        
             
 
     end
@@ -151,6 +162,11 @@ classdef TransmissionPerformance
                 netrates.KP4_hamming.NetRate      = NaN(1, numMeasurements);
                 netrates.KP4_hamming.CodeRate = NaN(1, numMeasurements);
                 netrates.KP4_hamming.Threshold = NaN(1, numMeasurements);
+
+                netrates.O_FEC.GrossRate      = NaN(1, numMeasurements);
+                netrates.O_FEC.NetRate      = NaN(1, numMeasurements);
+                netrates.O_FEC.CodeRate = NaN(1, numMeasurements);
+                netrates.O_FEC.Threshold = NaN(1, numMeasurements);
             end
             
             % Process each measurement individually.
@@ -204,6 +220,22 @@ classdef TransmissionPerformance
                         netrates.KP4_hamming.Threshold(i)    = obj.BERTHRESHOLDS_KP4_AND_INNER(idxBER);
                     end
 
+                    idxBER = [];
+                    for j = length(obj.BERTHRESHOLDS_O_FEC):-1:1
+                        if ber(i) <= obj.BERTHRESHOLDS_O_FEC(j)
+                            idxBER = j;
+                            break;
+                        end
+                    end
+                    if ~isempty(idxBER)
+                        codeRate = obj.CODE_RATE_O_FEC(idxBER);
+                        netrates.O_FEC.NetRate(i)      = grossRate(i) * codeRate;
+                        netrates.O_FEC.GrossRate(i)    = grossRate(i) ;
+                        netrates.O_FEC.CodeRate(i)     = codeRate;
+                        netrates.O_FEC.Threshold(i)    = obj.BERTHRESHOLDS_O_FEC(idxBER);
+                    end
+
+
 
                 end
 

Classes/DataBaseHandler/DBHandler.m

@@ -50,10 +50,10 @@ classdef DBHandler < handle
 
 
         function obj = refresh(obj)
-                % Get table names and the first rows of each table to understand the structure
-                obj.getTableNames();
-                obj.getTables();
-                obj.getDistinctValues();
+            % Get table names and the first rows of each table to understand the structure
+            obj.getTableNames();
+            obj.getTables();
+            obj.getDistinctValues();
         end
 
         function obj = getTableNames(obj)
@@ -187,10 +187,11 @@ classdef DBHandler < handle
             if isstruct(newRow)
                 fields = fieldnames(newRow);
                 emptyFields = structfun(@isempty,newRow);
-                if sum(emptyFields)>0
-                    newRow.(fields{emptyFields==1}) = NaN;
-                    disp(['In Table: ',tableName,': ',fields{emptyFields==1},' was empty, is now NaN ',newRow.(fields{emptyFields==1})])
-
+                if sum(emptyFields) > 0
+                    emptyFieldNames = fields(emptyFields);  % use () to get a cell array
+                    for idx = 1:numel(emptyFieldNames)
+                        newRow.(emptyFieldNames{idx}) = NaN;
+                    end
                 end
                 newRow = struct2table(newRow);
             end
@@ -274,87 +275,168 @@ classdef DBHandler < handle
             end
         end
 
-        function addBEREntry(obj, berValue, occurrence, runID, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, comment)
-            % addBEREntry Adds a BER entry linked to an existing or new Equalizer entry.
-            % Usage:
-            %   addBEREntry(runID, eq, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, berValue, comment)
 
-            if isempty(pf)
-                postfilter_taps = [];
+        function resultID = addProcessingResult(obj, run_id, resultData, eqParamsData)
+            % addProcessingResult Adds a processing result and links it to an EqualizerParameters entry.
+            %
+            % Inputs:
+            %   run_id: A run_id from the main table to connect the BER with.
+            %
+            %   resultData: A struct with fields corresponding to the ProcessingResults table.
+            %
+            %   eqParamsData: A struct with fields corresponding to the EqualizerParameters table,
+            %                 except 'eq_id' and 'config_hash'. These fields are used to compute
+            %                 a hash and check for an existing configuration.
+            %
+            % Output:
+            %   resultID: The result_id of the newly inserted ProcessingResults entry.
+
+            % 1. Compute hash for equalizer parameters
+            jsonStr = jsonencode(eqParamsData);
+            md = java.security.MessageDigest.getInstance('MD5');
+            md.update(uint8(jsonStr));
+            hashBytes = typecast(md.digest, 'uint8');
+            hashStr = lower(dec2hex(hashBytes)');
+            hashStr = lower(strtrim(hashStr(:)')); % Convert to a lowercase string
+
+            % Add hash to equalizer parameters
+            eqParamsData.config_hash = hashStr;
+
+            % 2. Check if an equalizer configuration with the same hash exists
+            queryStr = sprintf('SELECT eq_id FROM EqualizerParameters WHERE config_hash = ''%s''', eqParamsData.config_hash);
+            existingEntry = obj.fetch(queryStr);
+
+            if ~isempty(existingEntry)
+                % Use existing eq_id
+                eq_id = existingEntry{1,1};
             else
-                postfilter_taps = pf.burg_coeff;
+                % Insert the new equalizer configuration and get its eq_id
+                eq_id = obj.appendToTable('EqualizerParameters', eqParamsData);
             end
 
-            % Create equalizer data struct for searching and adding if necessary
-            equalizerData = struct( ...
-                'ffe', jsonencode(ffe), ...
-                'dfe', jsonencode(dfe), ...
-                'mlse', jsonencode(mlse), ...
-                'pf', jsonencode(pf), ...
-                'eq_type', string(eqType), ...
-                'ffe_order', jsonencode(ffe_order), ...
-                'dfe_order', jsonencode(dfe_order), ...
-                'postfilter_taps',jsonencode(postfilter_taps),...
-                'len_tr', len_tr, ...
-                'mu_ffe', jsonencode(mu_ffe), ...
-                'mu_dfe', mu_dfe, ...
-                'mu_dc', mu_dc, ...
-                'comment', comment ...
-                );
+            % 3. Add the equalizer configuration reference and run_id to resultData
+            resultData.eqParam_id = eq_id;
+            resultData.run_id = run_id;
 
-            % Check if exact Equalizer and BER entries already exist in the DB ...
-            selectedFields = {'Runs.run_id','BERs.ber_id','Equalizer.eq_id','BERs.ber',['BERs.occurrence' ...
-                '']};
-            filterParams = obj.tables;
-            filterParams.Equalizer = equalizerData;
-            [dataTable,sql_query] = obj.queryDB(filterParams, selectedFields);
+            % 4. Compute hash for the processing result
+            tempResultData = rmfield(resultData, 'date_of_processing');
+            resultJsonStr = jsonencode(tempResultData);
+            md2 = java.security.MessageDigest.getInstance('MD5');  % Create a new MD5 instance
+            md2.update(uint8(resultJsonStr));
+            resultHashBytes = typecast(md2.digest, 'uint8');
+            resultHashStr = lower(dec2hex(resultHashBytes)');
+            resultHashStr = lower(strtrim(resultHashStr(:)')); % Convert to a lowercase string
 
-            % get or insert Equalizer
-            if ~isempty(dataTable)
-                % Equalizer entry already exists, use the existing eq_id
-                cur_eq_id = dataTable.eq_id;
-            else
-                % Insert the new Equalizer entry
-                cur_eq_id = obj.appendToTable('Equalizer', equalizerData);
+            % Add the result hash to resultData
+            resultData.result_hash = resultHashStr;
+
+            % 5. Check if an identical processing result already exists
+            queryStr2 = sprintf('SELECT result_id FROM Results WHERE result_hash = ''%s''', resultData.result_hash);
+            existingResult = obj.fetch(queryStr2);
+
+            if ~isempty(existingResult)
+                % If the result exists, return its result_id without inserting a new row
+                resultID = existingResult{1,1};
+                warning(['Result already exists: ResultID: ',num2str(resultID),'| EQ ID: ',num2str(eq_id),' Run ID:  ' num2str(run_id)])
+                return;
             end
 
-            % skip if already here or insert BER entry
-            if ~isempty(dataTable)
+            % 6. Insert the processing result
+            resultID = obj.appendToTable('Results', resultData);
+        end
 
-                % A BER entry with the same eq_id, run_id, and occurrence already exists
-                existingBERValue = dataTable.ber;
+        function recalcHashes(obj)
+            % recalcHashes Recalculate hashes for all rows in the Results and EqualizerParameters tables.
+            %
+            % For EqualizerParameters, the hash is computed from all fields except
+            % 'eq_id' and 'config_hash'.
+            %
+            % For Results, the hash is computed from all fields except 'result_id',
+            % 'result_hash', and 'date_of_processing'.
 
-                % Compare the existing BER value with the new BER value
-                if existingBERValue == berValue
-                    fprintf('The BER entry %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists. \n',berValue, cur_eq_id, runID, occurrence);
-                else
-                    fprintf('Already found BER for EQ: %.2e ~= %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists.\n', berValue, existingBERValue, cur_eq_id, runID, occurrence);
+            % Recalculate hashes for EqualizerParameters
+            eqParamsRows = obj.fetch('SELECT * FROM EqualizerParameters');
+            for i = 1:height(eqParamsRows)
+                rowStruct = table2struct(eqParamsRows(i,:));  % Convert the table row to a struct
+
+                % Remove fields not part of the hash computation
+                if isfield(rowStruct, 'eq_id')
+                    rowStruct = rmfield(rowStruct, 'eq_id');
+                end
+                if isfield(rowStruct, 'config_hash')
+                    rowStruct = rmfield(rowStruct, 'config_hash');
                 end
 
-            else
-
-                % No such BER entry exists, insert the new BER entry
-                berData = struct( ...
-                    'run_id', runID, ...
-                    'eq_id', cur_eq_id, ...
-                    'ber', berValue, ...
-                    'occurrence', occurrence ...
-                    );
-
-                obj.appendToTable('BERs', berData);
+                % Compute MD5 hash from the JSON representation
+                jsonStr = jsonencode(rowStruct);
+                md = java.security.MessageDigest.getInstance('MD5');
+                md.update(uint8(jsonStr));
+                hashBytes = typecast(md.digest, 'uint8');
+                hashStr = lower(dec2hex(hashBytes)');
+                hashStr = lower(strtrim(hashStr(:)'));
 
+                % Update the config_hash field using the eq_id from the table row
+                eq_id = eqParamsRows.eq_id(i);
+                updateQuery = sprintf('UPDATE EqualizerParameters SET config_hash = ''%s'' WHERE eq_id = %d', hashStr, eq_id);
+                obj.executeSQL(updateQuery);
             end
 
+
+            % Fetch all rows from the Results table using queryDB with no filters
+            Results = obj.tables.Results;
+
+            if isstruct(Results)
+                newFields = {};
+                fNames = fieldnames(Results);
+                for i = 1:numel(fNames)
+                    newFields{end+1} = ['Results.' fNames{i}];
+                end
+                Results = newFields;
+            end
+            [resultsRows, ~] = obj.queryDB(obj.tables, Results);
+
+            for i = 1:height(resultsRows)
+                rowStruct = table2struct(resultsRows(i, :));  % Convert the row to a struct
+
+                % Remove fields not used in the hash calculation
+                if isfield(rowStruct, 'result_id')
+                    rowStruct = rmfield(rowStruct, 'result_id');
+                end
+                if isfield(rowStruct, 'result_hash')
+                    rowStruct = rmfield(rowStruct, 'result_hash');
+                end
+                if isfield(rowStruct, 'date_of_processing')
+                    rowStruct = rmfield(rowStruct, 'date_of_processing');
+                end
+
+                % Compute MD5 hash from the JSON representation
+                jsonStr = jsonencode(rowStruct);
+                md = java.security.MessageDigest.getInstance('MD5');
+                md.update(uint8(jsonStr));
+                hashBytes = typecast(md.digest, 'uint8');
+                hashStr = lower(dec2hex(hashBytes)');
+                hashStr = lower(strtrim(hashStr(:)'));
+
+                % Access the result_id from the table row and update the hash
+                result_id = resultsRows.result_id(i);
+                updateQuery = sprintf('UPDATE Results SET result_hash = ''%s'' WHERE result_id = %d', ...
+                    hashStr, result_id);
+                obj.executeSQL(updateQuery);
+            end
+
+
+
+
         end
 
 
 
+
         function executeSQL(obj, query)
             % This method executes an SQL statement using MATLAB's execute function.
             execute(obj.conn, query);
         end
 
-
         function answer = fetch(obj,query)
             answer = fetch(obj.conn,query);
         end
@@ -405,15 +487,46 @@ classdef DBHandler < handle
 
         function query = constructSQLQuery(obj, filterParams, selectedFields)
             % constructSQLQuery Constructs the SQL query based on filter parameters and selected fields.
+            %
+            % If selectedFields is provided as a struct, it is converted to a cell array.
+            % The conversion takes the field names and creates entries like:
+            %    {'selectedFields.fieldName'} for each field.
 
-            % Construct the SELECT clause dynamically based on user selection
+            % Input check for selectedFields: if it's a struct, convert it to a cell array.
+            if isstruct(selectedFields)
+                newFields = {};
+                tableNames = fieldnames(selectedFields);
+                for t = 1:numel(tableNames)
+                    tableStruct = selectedFields.(tableNames{t});
+                    fieldNames = fieldnames(tableStruct);
+                    for f = 1:numel(fieldNames)
+                        if isequal(tableStruct.(fieldNames{f}), 1)
+                            newFields{end+1} = sprintf('%s.%s', tableNames{t}, fieldNames{f});
+                        end
+                    end
+                end
+                selectedFields = newFields;
+            end
+
+            % Construct the SELECT clause dynamically based on user selection.
+            % (Assuming that when provided as a cell array, each entry is of the form
+            % 'TableName.fieldName' or, in our conversion case, 'selectedFields.fieldName'.)
             selectClause = 'SELECT DISTINCT ';
             for i = 1:numel(selectedFields)
                 fieldParts = strsplit(selectedFields{i}, '.');
-                tableName = fieldParts{1};
-                fieldName = fieldParts{2};
+                % If the field comes from the struct conversion, its first part is 'selectedFields'
+                % and the actual field name is in the second part.
+                if strcmp(fieldParts{1}, 'selectedFields')
+                    tableName = fieldParts{1};  % not used for type checking below
+                    fieldName = fieldParts{2};
+                else
+                    tableName = fieldParts{1};
+                    fieldName = fieldParts{2};
+                end
 
-                if isnumeric(obj.tables.(tableName).(fieldName))
+                % Decide on COALESCE depending on the field type.
+                % If the table is known in obj.tables and the field is numeric, use 'NaN'.
+                if isfield(obj.tables, tableName) && isfield(obj.tables.(tableName), fieldName) && isnumeric(obj.tables.(tableName).(fieldName))
                     selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', ''NaN'') AS ', fieldName];
                 else
                     selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', '''') AS ', fieldName];
@@ -426,235 +539,300 @@ classdef DBHandler < handle
                 end
             end
 
-            % Construct the FROM and WHERE clause
-            baseQuery = [selectClause, 'FROM Runs ' ...
-                'LEFT JOIN Configurations ON Runs.run_id = Configurations.run_id ' ...
-                'LEFT JOIN Measurements ON Runs.run_id = Measurements.run_id ' ...
-                'WHERE '];
-                % 'LEFT JOIN BERs ON Runs.run_id = BERs.run_id ' ...
-                % 'LEFT JOIN Equalizer ON BERs.eq_id = Equalizer.eq_id ' ...
+            % --- Adaptive FROM Clause ---
+            % Use "Runs" as the main table and add LEFT JOINs for every other table in obj.tables
+            % (except "sqlite_sequence") that has a run_id field.
+            mainTable = 'Runs';
+            fromClause = ['FROM ', mainTable, ' '];
+            tableNamesAll = fieldnames(obj.tables);
+            for t = 1:numel(tableNamesAll)
+                tableName = tableNamesAll{t};
+                if strcmpi(tableName, mainTable) || strcmpi(tableName, 'sqlite_sequence')
+                    continue;
+                end
 
+                if isfield(obj.tables.(tableName), 'run_id')
+                    % most tables are directly linked to runs table
+                    fromClause = [fromClause, 'LEFT JOIN ', tableName, ' ON ', mainTable, '.run_id = ', tableName, '.run_id '];
+                elseif isfield(obj.tables.(tableName), 'eq_id')
+                    % equalizer is only linked to results table
+                    fromClause = [fromClause, 'LEFT JOIN ', tableName, ' ON ', 'Results', '.eqParam_id = ', tableName, '.eq_id '];
+                end
+            end
 
-            % Loop through each table in filterParams
+            % --- WHERE Clause Construction ---
+            baseQuery = [selectClause, ' ', fromClause, 'WHERE '];
             filterClauses = [];
             tableNames_ = fieldnames(filterParams);
-
             for t = 1:numel(tableNames_)
                 tableName = tableNames_{t};
                 tableParams = filterParams.(tableName);
-
-                % Loop through each parameter in the table
                 fieldNames = fieldnames(tableParams);
                 for i = 1:numel(fieldNames)
                     fieldName = fieldNames{i};
                     value = tableParams.(fieldName);
-
-                    % Construct the full column name in the format "tableName.fieldName"
                     fullName = sprintf('%s.%s', tableName, fieldName);
 
-                    % Handle different types of values for SQL query construction
+                    % Handle various types of values for SQL query construction
                     if isempty(value)
-                        % Skip this parameter if it is empty (include all values)
                         continue;
                     elseif isnumeric(value) && isnan(value)
-                        % If value is NaN, use IS NULL in SQL
                         filterClause = sprintf('%s IS NULL', fullName);
                     elseif isnumeric(value) && ~isEnumeration(value)
                         filterClause = sprintf('%s = %f', fullName, value);
                     elseif islogical(value) || (isnumeric(value) && ismember(value, [0, 1])) && ~isEnumeration(value)
                         filterClause = sprintf('%s = %d', fullName, value);
                     elseif ischar(value) || isstring(value)
-                        filterClause = sprintf('%s = ''%s''', fullName, char(value)); %nicht nach string suchen sondern nach chararray -> 'bla' statt "bla"
+                        filterClause = sprintf('%s = ''%s''', fullName, char(value));
                     elseif isEnumeration(value)
                         filterClause = sprintf('%s = ''%s''', fullName, value);
                     else
                         error('Unsupported data type for field "%s".', fullName);
                     end
-
-                    % Add the constructed filter clause to the list
                     filterClauses = [filterClauses, filterClause, ' AND '];
                 end
             end
 
-            % Remove trailing ' AND ' from the filter clauses if any filters were added
+            % Remove trailing ' AND ' if any filters were added.
             if ~isempty(filterClauses)
                 filterClauses = filterClauses(1:end-5);
-            end
-
-            % Construct the final SQL query
-            if isempty(filterClauses)
-                query = [selectClause, 'FROM Runs ' ...
-                    'LEFT JOIN Configurations ON Runs.run_id = Configurations.run_id ' ...
-                    'LEFT JOIN Measurements ON Runs.run_id = Measurements.run_id ' ...
-                    'LEFT JOIN BERs ON Runs.run_id = BERs.run_id'];
+                query = [selectClause, ' ', fromClause, 'WHERE ', filterClauses];
             else
-                query = [baseQuery, filterClauses];
+                query = [selectClause, ' ', fromClause];
             end
-
         end
 
-
-
         function selectedFields = promptSelectFields(obj)
-            % promptSelectFields Prompts the user to select fields from multiple tables to include in the SELECT statement using settingsdlg.
+            % promptSelectFields Prompts the user to select fields from multiple tables
+            % using a custom checkbox GUI with scrolling.
+            %
+            % The function builds a list of all fields (formatted as 'TableName.fieldName')
+            % and displays each as a checkbox inside an inner container panel. The container's
+            % height is set to accommodate all checkboxes, so the scrollable panel shows scrollbars.
+            % When the user clicks the "Select" button, the selected fields are returned.
+            % If none are selected, all fields are returned.
 
-            % Get all possible fields from all tables (excluding sqlite_sequence)
+            % Get all possible tables (excluding sqlite_sequence)
             tableNames = fieldnames(obj.tables);
-            tableNames = setdiff(tableNames, {'sqlite_sequence'}); % Remove sqlite_sequence
-
-            % Prepare the inputs for settingsdlg
-            promptSettings = {};
-            allFieldsFullName = {};
-            convertedFieldNames = {};
+            tableNames = setdiff(tableNames, {'sqlite_sequence'});
 
+            % Build a single cell array of all field names with table prefix.
+            allFields = {};
             for i = 1:numel(tableNames)
-                tableFields = fieldnames(obj.tables.(tableNames{i}));
-                for j = 1:numel(tableFields)
-                    fieldName = tableFields{j};
-                    fullName = sprintf('%s.%s', tableNames{i}, fieldName);
-                    convertedName = strrep(fullName, '.', '_'); % Replace '.' with '_'
-
-                    allFieldsFullName{end + 1} = fullName; % Add full name to the list
-                    convertedFieldNames{end + 1} = convertedName; % Store the converted name
-
-                    % Add the field name and checkbox setting to the prompt
-                    promptSettings{end + 1} = {sprintf('Include %s', fullName), convertedName};
-                    promptSettings{end + 1} = false; % Default: not selected
+                fields = fieldnames(obj.tables.(tableNames{i}));
+                for j = 1:numel(fields)
+                    allFields{end+1} = sprintf('%s.%s', tableNames{i}, fields{j});
                 end
             end
+            numFields = numel(allFields);
 
-            % Create the settings dialog
-            [settings, button] = settingsdlg(...
-                'title', 'Select Fields for the SQL Query', ...
-                'description', 'Check the boxes for the fields you want to include in the SELECT statement.', ...
-                promptSettings{:} ...
-                );
+            % Create the main figure.
+            fig = uifigure('Name', 'Select Fields', 'Position', [100, 100, 400, 600]);
 
-            % If the user cancels, default to selecting all fields
-            if strcmp(button, 'cancel')
-                selectedFields = allFieldsFullName;
-                return;
+            % Create a scrollable panel.
+            scrollPanel = uipanel(fig, 'Position', [10, 60, 380, 530], 'Scrollable', 'on');
+
+            % Define checkbox dimensions.
+            checkboxHeight = 30;
+            spacing = 5;
+            totalHeight = numFields * (checkboxHeight + spacing);
+
+            % Create an inner container panel with height larger than the scrollPanel's height.
+            container = uipanel(scrollPanel, 'Position', [0, 0, scrollPanel.Position(3), totalHeight]);
+
+            % Create checkboxes using absolute positioning in the container.
+            checkboxes = gobjects(numFields, 1);
+            for i = 1:numFields
+                % Calculate the vertical position.
+                % The origin (0,0) is at the bottom left of the container.
+                yPos = totalHeight - i*(checkboxHeight + spacing) + spacing;
+                checkboxes(i) = uicheckbox(container, ...
+                    'Text', allFields{i}, ...
+                    'Value', false, ...
+                    'Position', [10, yPos, container.Position(3)-20, checkboxHeight]);
             end
 
-            % Parse user input into selectedFields
+            % Create a "Select" button in the main figure.
+            btn = uibutton(fig, 'Text', 'Select', ...
+                'Position', [150, 10, 100, 30], ...
+                'ButtonPushedFcn', @(btn, event) uiresume(fig));
+
+            % Wait for the user to click the button.
+            uiwait(fig);
+
+            % Retrieve the selected fields.
             selectedFields = {};
-            for i = 1:numel(allFieldsFullName)
-                convertedName = convertedFieldNames{i};
-                if isfield(settings, convertedName) && settings.(convertedName) % Add to selectedFields if the checkbox was selected
-                    selectedFields{end + 1} = allFieldsFullName{i}; %#ok<AGROW>
+            for i = 1:numFields
+                if checkboxes(i).Value
+                    selectedFields{end+1} = checkboxes(i).Text;
                 end
             end
 
-            % If no fields are selected, default to selecting all fields
+            % If no fields are selected, default to all fields.
             if isempty(selectedFields)
-                selectedFields = allFieldsFullName;
+                selectedFields = allFields;
             end
+
+            % Close the figure.
+            delete(fig);
         end
 
         function filterParams = promptFilterParameters(obj)
-            % promptFilterParameters Prompts the user to enter filter parameters using the settingsdlg framework.
+            % promptFilterParameters Prompts the user to enter filter parameters using a
+            % custom scrollable UI with dropdowns.
+            %
+            % For each table (excluding 'sqlite_sequence'), each field that has distinct
+            % values is displayed as a label and a dropdown. The dropdown items are built
+            % from the distinct values (with "All" prepended). The output is a struct where,
+            % for each table, each field is set to the chosen value (or [] if "All" is selected).
 
-            % Get all possible parameters from all tables (excluding sqlite_sequence)
-            tableNames_ = fieldnames(obj.tables);
-            tableNames_ = setdiff(tableNames_, {'sqlite_sequence'}); % Remove sqlite_sequence
+            % Get all tables except 'sqlite_sequence'
+            tableNames = fieldnames(obj.tables);
+            tableNames = setdiff(tableNames, {'sqlite_sequence'});
 
-            % Prepare the inputs for settingsdlg with sections and separators
-            promptSettings = {};
-            allFieldsFullName = {};
-            convertedFieldNames = {};
+            % Precompute layout constants.
+            heightPerTableLabel = 30;
+            heightPerField = 40; % vertical space for a field (label + dropdown)
+            spacing = 5;
 
-            for i = 1:numel(tableNames_)
-                % Add a separator for each table section
-                promptSettings{end + 1} = 'separator';
-                promptSettings{end + 1} = tableNames_{i};
-
-                % Get all fields from the current table
-                tableFields = fieldnames(obj.tables.(tableNames_{i}));
-
-                % Prepare each field to be added to the dialog
+            % Compute total required height.
+            totalHeight = 0;
+            for i = 1:numel(tableNames)
+                totalHeight = totalHeight + heightPerTableLabel;
+                tableName = tableNames{i};
+                tableFields = fieldnames(obj.tables.(tableName));
                 for j = 1:numel(tableFields)
                     fieldName = tableFields{j};
-                    fullName = sprintf('%s.%s', tableNames_{i}, fieldName);
-                    convertedName = strrep(fullName, '.', '_'); % Replace '.' with '_'
-
-                    % Skip fields that do not have distinct values stored
-                    if ~isfield(obj.distinctValues.(tableNames_{i}), fieldName)
-                        continue;
+                    % Only include fields that have distinct values stored.
+                    if isfield(obj.distinctValues.(tableName), fieldName)
+                        totalHeight = totalHeight + heightPerField;
                     end
-
-                    % Get the distinct values for the field
-                    distinctValues_ = obj.distinctValues.(tableNames_{i}).(fieldName);
-
-                    % Prepare distinct values for dropdown
-                    if isempty(distinctValues_)
-                        % If there are no distinct values, use only an "All" entry
-                        distinctValues_ = {'All'};
-                    else
-                        % Ensure distinctValues is a cell array of strings
-                        if isnumeric(distinctValues_)
-                            distinctValues_ = arrayfun(@(x) num2str(x), distinctValues_, 'UniformOutput', false);
-                        elseif isstring(distinctValues_)
-                            distinctValues_ = cellstr(distinctValues_);
-                        elseif iscell(distinctValues_) && ~iscellstr(distinctValues_)
-                            distinctValues_ = cellfun(@num2str, distinctValues_, 'UniformOutput', false);
-                        end
-
-                        % Add an "All" option at the beginning of the distinct values list
-                        distinctValues_ = [{'All'}; distinctValues_];
-                    end
-
-                    allFieldsFullName{end + 1} = fullName; % Add full name to the list
-                    convertedFieldNames{end + 1} = convertedName; % Store the converted name
-
-                    % Add the field name and value setting to the prompt
-                    promptSettings{end + 1} = {sprintf('%s', fullName), convertedName};
-                    promptSettings{end + 1} = distinctValues_; % Add distinct values as dropdown options
                 end
             end
 
-            % Create the settings dialog
-            [settings, button] = settingsdlg(...
-                'title', 'Input Parameters for Filtering', ...
-                'description', 'Enter the values for each field to filter. Select "All" to include all values.', ...
-                promptSettings{:} ...
-                );
+            % Create the main UI figure.
+            fig = uifigure('Name', 'Input Parameters for Filtering', 'Position', [100, 100, 500, 600]);
 
-            % If the user cancels, return an empty struct
-            if strcmp(button, 'cancel')
+            % Set a CloseRequestFcn so that closing the figure calls uiresume.
+            fig.CloseRequestFcn = @(src, event) uiresume(src);
+
+            % Create a scrollable panel inside the figure.
+            scrollPanel = uipanel(fig, 'Position', [10, 60, 480, 530], 'Scrollable', 'on');
+
+            % Create an inner container panel with a height set to totalHeight.
+            container = uipanel(scrollPanel, 'Position', [0, 0, scrollPanel.Position(3), totalHeight]);
+
+            % Prepare cell arrays to store dropdown handles and corresponding table/field names.
+            dropdownHandles = {};
+            dropdownTableNames = {};
+            dropdownFieldNames = {};
+
+            % Set the starting Y coordinate (filling from top to bottom).
+            currentY = totalHeight;
+
+            % Maximum number of dropdown items.
+            maxItems = 100;
+
+            for i = 1:numel(tableNames)
+                % Create a label for the table name.
+                uilabel(container, ...
+                    'Text', tableNames{i}, ...
+                    'FontWeight', 'bold', ...
+                    'Position', [10, currentY - heightPerTableLabel + spacing, 200, heightPerTableLabel - spacing]);
+                currentY = currentY - heightPerTableLabel;
+
+                tableName = tableNames{i};
+                tableFields = fieldnames(obj.tables.(tableName));
+                for j = 1:numel(tableFields)
+                    fieldName = tableFields{j};
+                    if ~isfield(obj.distinctValues.(tableName), fieldName)
+                        continue;  % Skip if no distinct values are stored.
+                    end
+
+                    % Retrieve distinct values for the field.
+                    distinctValues_ = obj.distinctValues.(tableName).(fieldName);
+                    if ~isempty(distinctValues_) && numel(distinctValues_) > maxItems
+                        distinctValues_ = distinctValues_(1:maxItems);
+                    end
+
+                    if isempty(distinctValues_)
+                        items = {'All'};
+                    else
+                        if isnumeric(distinctValues_)
+                            items = cellfun(@num2str, num2cell(distinctValues_), 'UniformOutput', false);
+                        elseif isstring(distinctValues_)
+                            items = cellstr(distinctValues_);
+                        elseif iscell(distinctValues_) && ~iscellstr(distinctValues_)
+                            items = cellfun(@num2str, distinctValues_, 'UniformOutput', false);
+                        else
+                            items = distinctValues_;
+                        end
+                        items = items(:)';  % Ensure row vector
+                        items = [{'All'}, items];
+                    end
+
+                    % Create a label for the field.
+                    uilabel(container, ...
+                        'Text', sprintf('%s:', fieldName), ...
+                        'HorizontalAlignment', 'right', ...
+                        'Position', [10, currentY - 25, 150, 25]);
+
+                    % Create a dropdown for the field.
+                    dd = uidropdown(container, ...
+                        'Items', items, ...
+                        'Value', 'All', ...
+                        'Position', [170, currentY - 25, 200, 25]);
+
+                    % Store the dropdown handle and its associated table/field.
+                    dropdownHandles{end+1} = dd;
+                    dropdownTableNames{end+1} = tableName;
+                    dropdownFieldNames{end+1} = fieldName;
+
+                    currentY = currentY - heightPerField;
+                end
+            end
+
+            % Create a "Submit" button at the bottom of the figure.
+            btn = uibutton(fig, 'Text', 'Submit', ...
+                'Position', [200, 10, 100, 30], ...
+                'ButtonPushedFcn', @(btn, event) uiresume(fig));
+
+            % Wait until the user clicks "Submit" or closes the figure.
+            uiwait(fig);
+
+            % If the figure was closed (and thus no longer valid), return an empty struct.
+            if ~isvalid(fig)
                 filterParams = struct();
                 return;
             end
 
-            % Parse user input into filterParams structure
+            % Build the filterParams struct from the dropdown selections.
             filterParams = struct();
-
-            for i = 1:numel(allFieldsFullName)
-                value = settings.(convertedFieldNames{i});
-
-                % Split full name to get table and field names
-                fieldParts = strsplit(allFieldsFullName{i}, '.');
-                tableName = fieldParts{1};
-                fieldName = fieldParts{2};
-
-                % If the table does not exist in the filterParams struct, create it
+            for k = 1:numel(dropdownHandles)
+                tableName = dropdownTableNames{k};
+                fieldName = dropdownFieldNames{k};
+                value = dropdownHandles{k}.Value;
                 if ~isfield(filterParams, tableName)
                     filterParams.(tableName) = struct();
                 end
 
-                % Assign values to the respective fields under each table
+                % If "All" is selected, assign empty; otherwise, try converting to numeric.
                 if strcmp(value, 'All')
-                    filterParams.(tableName).(fieldName) = []; % Set to empty to include all values
-                elseif isnumeric(value) && isnan(value)
-                    filterParams.(tableName).(fieldName) = NaN; % Use NaN to handle as NULL
+                    filterParams.(tableName).(fieldName) = [];
                 else
-                    filterParams.(tableName).(fieldName) = value; % Use the entered value
+                    numValue = str2double(value);
+                    if ~isnan(numValue)
+                        filterParams.(tableName).(fieldName) = numValue;
+                    else
+                        filterParams.(tableName).(fieldName) = value;
+                    end
                 end
             end
+
+            % Close the figure.
+            delete(fig);
         end
 
 
-
-
-
     end
 end

Classes/Moveit_wrapper.m

@@ -0,0 +1,180 @@
+classdef Moveit_wrapper < handle
+    %
+
+    properties(Access=public)
+        moveit_function_name
+        para
+        state = struct()
+        comment
+    end
+
+    methods (Access=public)
+        function obj = Moveit_wrapper(moveit_function_name,options)
+            %
+
+            arguments
+                moveit_function_name
+                options.para
+            end
+
+            obj.moveit_function_name = moveit_function_name;
+            fn = fieldnames(options);
+            for n = 1:numel(fn)
+                try
+                    obj.(fn{n}) = options.(fn{n});
+                end
+            end
+
+            % Ensure the function exists
+            if ~exist(obj.moveit_function_name, 'file')
+                error('Function "%s" does not exist.', obj.moveit_function_name);
+            end
+
+            % Step 1: Get default parameters by calling moveit module
+            if isempty(obj.para)
+                global loop;
+                loop = 0;  % Request parameter structure
+                [obj.para, obj.comment] = feval(obj.moveit_function_name);
+            end
+
+        end
+
+        function signal_out = process(obj,signal_in)
+
+            arguments
+                obj 
+                signal_in = []
+                
+            end
+
+            isSignalClass = 0;
+            if isa(signal_in,"Signal")
+                signal_out = signal_in;
+                signal_in = signal_in.signal;
+                isSignalClass = 1;
+            end
+
+            % signal_in = signal_in.';
+
+            % INIT MOVEIT
+            global loop;
+            loop = 0;
+            signal_out = obj.moveit_init(signal_in);
+
+            % RUN MOVEIT
+            global loop;
+            loop = 1;
+
+            signal_out = obj.moveit_init(signal_out);
+
+            if isSignalClass
+                % append to logbook
+                lbdesc = ['Logbookentry'];
+                signal_out  = signal_out.logbookentry(lbdesc);
+                signal_out.signal = signal_out;
+            end
+
+        end
+
+        function open_settings(obj)
+            % Opens a settings dialog for modifying Moveit parameters with appropriate input types.
+            % Inserts separators when the level value changes.
+
+            fieldNames = fieldnames(obj.para);
+            settingsCell = {};
+            previousLevel = -inf; % Track previous level for separators
+
+            % Create input arguments for settingsdlg
+            for i = 1:numel(fieldNames)
+                fieldName = fieldNames{i};
+                value = obj.para.(fieldName);
+
+                % Get description from comment structure if available
+                if isfield(obj.comment, fieldName)
+                    description = obj.comment.(fieldName);
+                else
+                    description = fieldName; % Default to field name if no description
+                end
+
+                % Get level for this parameter
+                if isfield(obj.comment.level, fieldName)
+                    currentLevel = obj.comment.level.(fieldName);
+                else
+                    currentLevel = 1; % Default level
+                end
+
+                % Insert separator if the level changes
+                if currentLevel ~= previousLevel
+                    settingsCell{end+1} = 'separator';
+                    settingsCell{end+1} = ['Level ', num2str(currentLevel)];
+                end
+                previousLevel = currentLevel;
+
+                % Determine input type from obj.comment.type
+                if  1
+                    inputType = obj.comment.type.(fieldName);
+                else
+                    inputType = 'number'; % Default type
+                end
+
+                % Add field description
+                settingsCell{end+1} = {description; fieldName};
+
+                % Define the input type
+                if strcmp(inputType, 'boolean')
+                    % Checkbox input
+                    settingsCell{end+1} = logical(value);                   % Enable checkbox
+                elseif contains(inputType, '|')
+                    % Dropdown selection (options separated by '|')
+                    dropdownOptions = strsplit(inputType, '|');
+                    settingsCell{end+1} = dropdownOptions;
+                else
+                    % Default: Numeric input
+                    settingsCell{end+1} = value;
+                end
+            end
+
+            % Open settings dialog
+            [newValues, button] = settingsdlg(...
+                'title', ['Settings: ', obj.moveit_function_name], ...
+                'description', ['Adjust parameters for ', obj.moveit_function_name], ...
+                settingsCell{:} ...
+                );
+
+            % Update obj.para with new values only if "OK" was pressed
+            if strcmp(button, 'OK')
+                fieldNames = fieldnames(newValues);
+                for i = 1:numel(fieldNames)
+                    if fieldNames{i}
+
+                    end
+                    obj.para.(fieldNames{i}) = newValues.(fieldNames{i});
+                end
+            end
+        end
+
+    end
+
+
+    methods (Access=private)
+
+        function data_out = moveit_init(obj,data_in)
+            arguments(Input)
+                obj
+                data_in double
+            end
+            % Step 2: Initialize the function
+            [data_out, obj.state] = feval(obj.moveit_function_name, data_in, obj.state, obj.para);
+        end
+
+        function data_out = moveit_simulation_computation(obj,data_in)
+            arguments(Input)
+                obj
+                data_in double
+            end
+            % Step 3: Process input signal
+            [data_out, obj.state] = feval(obj.moveit_function_name, data_in, obj.state, obj.para);
+        end
+
+    end
+end

Classes/Warehouse_class/classes/DataStorage.m

@@ -89,7 +89,7 @@ classdef DataStorage < handle
             for p = 1:numel(obj.fn)
                 name = obj.fn(p);
                 values = obj.inputParams.(name);
-                obj.parameter.(name) = Parameter(name,values);
+                obj.parameter.(name) = StorageParameter(name,values);
             end
 
         end

Classes/Warehouse_class/classes/StorageParameter.m

@@ -1,4 +1,4 @@
-classdef Parameter < handle
+classdef StorageParameter < handle
     %PARAMETER Summary of this class goes here
     %   Detailed explanation goes here
 
@@ -12,7 +12,7 @@ classdef Parameter < handle
     end
 
     methods
-        function obj = Parameter(name, values)
+        function obj = StorageParameter(name, values)
             %PARAMETER Construct 
             obj.name        = name;
             obj.values      = values;

Datatypes/clr.m

@@ -0,0 +1,70 @@
+classdef clr
+    properties (Constant)
+        % Set1 colormap
+        Set1 = struct( ...
+            'red',     [0.8941, 0.1020, 0.1098], ...
+            'blue',    [0.2157, 0.4941, 0.7216], ...
+            'green',   [0.3020, 0.6863, 0.2902], ...
+            'purple',  [0.5961, 0.3059, 0.6392], ...
+            'orange',  [1.0000, 0.4980, 0.0000], ...
+            'yellow',  [1.0000, 1.0000, 0.2000], ...
+            'brown',   [0.6510, 0.3373, 0.1569], ...
+            'pink',    [0.9686, 0.5059, 0.7490], ...
+            'gray',    [0.6000, 0.6000, 0.6000]);
+
+        % Paired colormap
+        Paired = struct( ...
+            'lightblue',  [0.6510, 0.8078, 0.8902], ...
+            'blue',       [0.1216, 0.4706, 0.7059], ...
+            'lightgreen', [0.6980, 0.8745, 0.5412], ...
+            'green',      [0.2000, 0.6275, 0.1725], ...
+            'lightred',   [0.9843, 0.6039, 0.6000], ...
+            'red',        [0.8902, 0.1020, 0.1098], ...
+            'lightorange',[0.9922, 0.7490, 0.4353], ...
+            'orange',     [1.0000, 0.4980, 0.0000], ...
+            'lightpurple',[0.7922, 0.6980, 0.8392], ...
+            'purple',     [0.4157, 0.2392, 0.6039], ...
+            'lightyellow',[1.0000, 1.0000, 0.6000], ...
+            'brown',      [0.6941, 0.3490, 0.1569]);
+
+    end
+
+    methods (Static)
+        function showRGB(colorArray, names)
+            % Visualize colors in a horizontal bar chart
+            if nargin < 2
+                names = repmat({''}, size(colorArray, 1), 1);
+            end
+
+            figure;
+            hold on;
+            for i = 1:size(colorArray, 1)
+                fill([0 1 1 0], [i-1 i-1 i i], colorArray(i, :), 'EdgeColor', 'k');
+                text(1.1, i-0.5, names{i}, 'FontSize', 12, 'Interpreter', 'none');
+            end
+            ylim([0, size(colorArray, 1)]);
+            xlim([0, 1.5]);
+            axis off;
+            title('Color Preview');
+            hold off;
+        end
+
+        function showSet(colorStruct)
+            % Show colors from a structure in a bar plot
+            names = fieldnames(colorStruct);
+            colors = cell2mat(struct2cell(colorStruct)');
+
+            figure;
+            hold on;
+            for i = 1:size(colors, 1)
+                fill([0 1 1 0], [i-1 i-1 i i], colors(i, :), 'EdgeColor', 'k');
+                text(1.1, i-0.5, names{i}, 'FontSize', 12, 'Interpreter', 'none');
+            end
+            ylim([0, size(colors, 1)]);
+            xlim([0, 1.5]);
+            axis off;
+            title('Color Preview');
+            hold off;
+        end
+    end
+end

Datatypes/equalizer_structure.m

@@ -4,7 +4,8 @@ classdef equalizer_structure < int32
         ffe             (0)
         vnle            (1)
         vnle_pf_mlse    (2)
-        db_precoded     (3)
+        % db_precoded     (3)
+        vnle_db_mlse    (3)
         db_encoded 	    (4)
     end
 

Datatypes/pulseform.m

@@ -1,7 +1,8 @@
 classdef pulseform < int32
 
    enumeration
-      rrc (1)
+      rc  (2) %raised cosine (use this at Tx without matched filter)
+      rrc (1) %root raised cosine (usually with matched filter)
    end
    
 end

Functions/EQ_structures/duobinary_signaling.m

@@ -1,18 +1,96 @@
-function [eq_package] =  duobinary_signaling(eq_, mlse_,M ,rx_signal, tx_symbols, tx_bits)
-    %Duobinary Signaling
+function [eq_package] =  duobinary_signaling(eq_, mlse_,M ,rx_signal, tx_symbols, tx_bits,options)
+%Duobinary Signaling
+arguments
+    eq_ 
+    mlse_ 
+    M 
+    rx_signal 
+    tx_symbols 
+    tx_bits 
+    options.postFFE = [];
+end
 
-    [eq_signal, eq_noise] = eq_.process(rx_signal,tx_symbols);
 
-    eq_signal = mlse_.process(eq_signal);
+[eq_signal, eq_noise] = eq_.process(rx_signal,tx_symbols);
 
-    eq_signal = Duobinary().encode(eq_signal);
-    eq_signal = Duobinary().decode(eq_signal);
+if ~isempty(options.postFFE)
+    [eq_signal,eq_noise] = options.postFFE.process(eq_signal,tx_symbols);
+end
 
-    % M = numel(unique(eq_signal.signal));
-    rx_bits = PAMmapper(M,0).demap(eq_signal);
 
-    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+eq_signal = mlse_.process(eq_signal);
 
-    eq_package.ber = ber;
+eq_signal = Duobinary().encode(eq_signal);
+eq_signal = Duobinary().decode(eq_signal);
+
+% M = numel(unique(eq_signal.signal));
+rx_bits = PAMmapper(M,0).demap(eq_signal);
+
+[bits_db,errors_db,ber_db,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+
+eq_package.ber = ber_db;
+
+resultsDBsignaling = struct( ...
+    'result_id',    NaN, ...  %
+    'run_id',       NaN, ...  % Beispielhafte Run-ID
+    'eqParam_id',   NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
+    'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
+    'numBits',      bits_db, ... % Beispiel: 1.000.000 Bits
+    'numBitErr',    errors_db, ... % Beispiel: 120 Bitfehler
+    'BER_precoded', [], ... % BER = 120 / 1.000.000
+    'numBitErr_precoded', [], ... % Beispiel: 120 Bitfehler
+    'BER',          ber_db, ... % BER = 120 / 1.000.000
+    'SNR',          [], ... % Beispielhafte SNR
+    'SNR_level',    jsonencode([]), ... % SNR-Level als JSON-codiertes Array
+    'GMI',          [], ... % Beispielhafter GMI-Wert
+    'AIR',          [], ... % Beispielhafter AIR-Wert
+    'EVM',          [], ... % Beispielhafte EVM
+    'EVM_level',    jsonencode([]), ... % EVM-Level als JSON-codiertes Array
+    'Alpha',        [] ... % Beispielhafter Alpha-Wert
+    );
+
+if ~isempty(options.postFFE)
+    npostFFE = options.postFFE.order;
+else
+    npostFFE = 0;
+end
+
+equalizerConfigDBsignaling = struct( ...
+    'eq_id',        NaN, ...  % Auto-Inkrement, wird in der DB gesetzt
+    'equalizer_structure', int32(equalizer_structure.db_encoded), ...  % Beispiel: 1 (z.B. für vnle)
+    'M',            M, ...  % Ordnung der PAM-Konstellation
+    'target_constellation', jsonencode(round(unique(tx_symbols.signal),5)), ...  % Beispielhafter Target-String
+    'db_target',     1, ...  % 0 oder 1
+    'diff_precode',  1, ...  % 0 oder 1
+    'postFFE',      ~isempty(options.postFFE), ...  % Beispielwert
+    'NpostFFE',     npostFFE, ...  % Beispielwert
+    'Ne1',          eq_.Ne(1), ...  % Feedforward Koeffizienten 1. Ordnung
+    'Ne2',          eq_.Ne(2), ...   % Feedforward Koeffizienten 2. Ordnung
+    'Ne3',          eq_.Ne(3), ...   % Feedforward Koeffizienten 3. Ordnung
+    'Nb1',          eq_.Nb(1), ...   % Decision Feedback Koeffizienten 1. Ordnung
+    'Nb2',          eq_.Nb(2), ...   % Decision Feedback Koeffizienten 2. Ordnung
+    'Nb3',          eq_.Nb(3), ...   % Decision Feedback Koeffizienten 3. Ordnung
+    'K',            eq_.K, ...     % Samples pro Symbol
+    'DCmu',         eq_.DCmu, ...  % Anpassungsrate für DC-Tap
+    'ideal_dfe',    eq_.ideal_dfe, ... % Flag für ideal DFE (0 oder 1)
+    'training_length', eq_.training_length, ...  % Anzahl Trainingssymbole
+    'training_loops', eq_.training_loops, ...  % Anzahl Trainingsdurchläufe
+    'TRmu1',        eq_.FFEmu, ...  % mu für DD-Modus (1. Ordnung)
+    'TRmu2',        eq_.FFEmu, ...  % mu für DD-Modus (2. Ordnung)
+    'TRmu3',        eq_.FFEmu, ...  % mu für DD-Modus (3. Ordnung)
+    'TRmuDFE',      eq_.DFEmu, ... % mu für DFE-Modus im DD
+    'dd_loops',     5, ...  % Anzahl Durchläufe im DD-Modus
+    'DDmu1',        eq_.DDmu(1), ...  % mu für DD-Modus (1. Ordnung)
+    'DDmu2',        eq_.DDmu(2), ...  % mu für DD-Modus (2. Ordnung)
+    'DDmu3',        eq_.DDmu(3), ...  % mu für DD-Modus (3. Ordnung)
+    'DDmuDFE',      eq_.DDmu(4), ... % mu für DFE-Modus im DD
+    'MLSE_mode',    'viterbi', ...  % Beispiel: MLSE-Modus als String
+    'MLSE_trellis_states', jsonencode(mlse_.trellis_states), ...  % Trellis-States, z.B. als JSON-String oder kommasepariert
+    'comment',      'function: duobinary_target.m', ...  % Zusätzliche Kommentare
+    'config_hash',  NaN ...
+    );
+
+eq_package.resultsDBsignaling = resultsDBsignaling;
+eq_package.equalizerConfigDBsignaling = equalizerConfigDBsignaling;
 
 end

Functions/EQ_structures/duobinary_target.m

@@ -9,69 +9,148 @@ arguments
     tx_bits
     options.precode_mode db_mode
     options.showAnalysis = 0;
+    options.eth_style_symbol_mapping = 0;
+    options.postFFE = [];
 end
 
-    %Duobinary Targeting
+%Duobinary Targeting
+db_ref_sequence = Duobinary().encode(tx_symbols);
+db_ref_constellation = unique(db_ref_sequence.signal);
+[eq_signal, eq_noise] = eq_.process(rx_signal,db_ref_sequence);
 
-    [eq_signal, eq_noise] = eq_.process(rx_signal,Duobinary().encode(tx_symbols));
+if ~isempty(options.postFFE)
+    [eq_signal,eq_noise] = options.postFFE.process(eq_signal,db_ref_sequence);
+end
 
-    % dir = [1,1];
-    mlse_sig_sd = mlse_.process(eq_signal);
+% dir = [1,1];
+mlse_sig_sd = mlse_.process(eq_signal);
 
-    mlse_sig_hd = PAMmapper(M,0).quantize(mlse_sig_sd);
+mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
 
-    % precoding to mitigate error propagation, most prominently used in
-    % combination with duobinary signaling to avoid catastrophic error
-    % behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
+% precoding to mitigate error propagation, most prominently used in
+% combination with duobinary signaling to avoid catastrophic error
+% behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
+switch options.precode_mode
 
-    % takes: 
-    %   -> eq_signal_hd: hard decision signal after eq
-    %   -> tx_symbols: that where used as reference for eq 
+    case db_mode.no_db
+        % TX Data is not precoded:
 
-    switch options.precode_mode
-        case db_mode.db_emulate
-
-        mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
-        mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
+        % A) Emulate diff precoding
+        mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
+        mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
 
         tx_symbols_precoded = Duobinary().encode(tx_symbols);
         tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
 
-        tx_bits = PAMmapper(M,0).demap(tx_symbols_precoded);
+        tx_bits_precoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
 
-        case db_mode.db_discard
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_precoded);
+        [~,errors_db_diff_precoded,ber_db_diff_precoded,~]  = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        % normal dsp for precoded sequence == discard/omit/ignore precode
-        tx_bits = PAMmapper(M,0).demap(tx_symbols);
+        %B) Just determine BER
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
+        [bits_mlse,errors_mlse,ber_db,~]  = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        case db_mode.db_encoded
+    case db_mode.db_precoded
 
-        % normal DB encoded data (only for 10KM)
+        % Daten SIND TATSÄCHLICH precoded auf TX Seite:
 
-        case db_mode.db_precoded
+        % A) Decode at Rx if no DB targeting was applied (we are in VNLE or MLSE EQ structure here!
+        mlse_sig_hd_decoded = Duobinary().encode(mlse_sig_hd,"M",M);
+        mlse_sig_hd_decoded = Duobinary().decode(mlse_sig_hd_decoded,"M",M);
+        rx_bits_mlse_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_decoded);
+        [~,errors_db_diff_precoded,ber_db_diff_precoded,~]  = calc_ber(rx_bits_mlse_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
-        mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
+        % B) Omit the Coding by comparing with demapped TX symbol sequence
 
-    end
+        tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols);
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
+        [bits_db,errors_db,ber_db,~]  = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-    % M = numel(unique(tx_symbols.signal));
-    rx_bits = PAMmapper(M,0).demap(mlse_sig_hd);
+end
 
-    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+% M = numel(unique(tx_symbols.signal));
+rx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
 
+[bits_db,errors_db,ber_db,errorIndice_db] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+eq_package.ber          = ber_db;
 
-    eq_package.ber          = ber;
+resultsDBtgt = struct( ...
+    'result_id',    NaN, ...  %
+    'run_id',       NaN, ...  % Beispielhafte Run-ID
+    'eqParam_id',   NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
+    'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
+    'numBits',      bits_db, ... % Beispiel: 1.000.000 Bits
+    'numBitErr',    errors_db, ... % Beispiel: 120 Bitfehler
+    'BER_precoded', ber_db_diff_precoded, ... % BER = 120 / 1.000.000
+    'numBitErr_precoded', errors_db_diff_precoded, ... % Beispiel: 120 Bitfehler
+    'BER',          ber_db, ... % BER = 120 / 1.000.000
+    'SNR',          [], ... % Beispielhafte SNR
+    'SNR_level',    jsonencode([]), ... % SNR-Level als JSON-codiertes Array
+    'GMI',          [], ... % Beispielhafter GMI-Wert
+    'AIR',          [], ... % Beispielhafter AIR-Wert
+    'EVM',          [], ... % Beispielhafte EVM
+    'EVM_level',    jsonencode([]), ... % EVM-Level als JSON-codiertes Array
+    'Alpha',        [] ... % Beispielhafter Alpha-Wert
+    );
 
-    if options.showAnalysis
-        eq_noise = eq_noise - mean(eq_noise.signal);
+if ~isempty(options.postFFE)
+    npostFFE = options.postFFE.order;
+else
+    npostFFE = 0;
+end
 
-rx_signal.spectrum("normalizeTo0dB",1,"fignum",250);
+equalizerConfigDBtgt = struct( ...
+    'eq_id',        NaN, ...  % Auto-Inkrement, wird in der DB gesetzt
+    'equalizer_structure', int32(equalizer_structure.vnle_db_mlse), ...  % Beispiel: 1 (z.B. für vnle)
+    'M',            M, ...  % Ordnung der PAM-Konstellation
+    'target_constellation', jsonencode(round(db_ref_constellation,5)), ...  % Beispielhafter Target-String
+    'db_target',    1, ...  % 0 oder 1
+    'diff_precode',  int32(options.precode_mode), ...  % 0 oder 1
+    'postFFE',      ~isempty(options.postFFE), ...  % Beispielwert
+    'NpostFFE',     npostFFE, ...  % Beispielwert
+    'Ne1',          eq_.Ne(1), ...  % Feedforward Koeffizienten 1. Ordnung
+    'Ne2',          eq_.Ne(2), ...   % Feedforward Koeffizienten 2. Ordnung
+    'Ne3',          eq_.Ne(3), ...   % Feedforward Koeffizienten 3. Ordnung
+    'Nb1',          eq_.Nb(1), ...   % Decision Feedback Koeffizienten 1. Ordnung
+    'Nb2',          eq_.Nb(2), ...   % Decision Feedback Koeffizienten 2. Ordnung
+    'Nb3',          eq_.Nb(3), ...   % Decision Feedback Koeffizienten 3. Ordnung
+    'K',            eq_.K, ...     % Samples pro Symbol
+    'DCmu',         eq_.DCmu, ...  % Anpassungsrate für DC-Tap
+    'ideal_dfe',    eq_.ideal_dfe, ... % Flag für ideal DFE (0 oder 1)
+    'training_length', eq_.training_length, ...  % Anzahl Trainingssymbole
+    'training_loops', eq_.training_loops, ...  % Anzahl Trainingsdurchläufe
+    'TRmu1',        eq_.FFEmu, ...  % mu für DD-Modus (1. Ordnung)
+    'TRmu2',        eq_.FFEmu, ...  % mu für DD-Modus (2. Ordnung)
+    'TRmu3',        eq_.FFEmu, ...  % mu für DD-Modus (3. Ordnung)
+    'TRmuDFE',      eq_.DFEmu, ... % mu für DFE-Modus im DD
+    'dd_loops',     5, ...  % Anzahl Durchläufe im DD-Modus
+    'DDmu1',        eq_.DDmu(1), ...  % mu für DD-Modus (1. Ordnung)
+    'DDmu2',        eq_.DDmu(2), ...  % mu für DD-Modus (2. Ordnung)
+    'DDmu3',        eq_.DDmu(3), ...  % mu für DD-Modus (3. Ordnung)
+    'DDmuDFE',      eq_.DDmu(4), ... % mu für DFE-Modus im DD
+    'MLSE_mode',    'viterbi', ...  % Beispiel: MLSE-Modus als String
+    'MLSE_trellis_states', jsonencode(mlse_.trellis_states), ...  % Trellis-States, z.B. als JSON-String oder kommasepariert
+    'comment',      'function: duobinary_target.m', ...  % Zusätzliche Kommentare
+    'config_hash',  NaN ...
+    );
 
-        showEQNoisePSD(eq_noise,"fignum",250,"displayname",'Duobinary Target Noise');
+eq_package.resultsDBtgt          = resultsDBtgt;
+eq_package.equalizerConfigDBtgt          = equalizerConfigDBtgt;
 
-          Duobinary().encode(tx_symbols).spectrum("normalizeTo0dB",1,"fignum",250);
-    end
+if options.showAnalysis
+    eq_noise = eq_noise - mean(eq_noise.signal);
+
+    rx_signal.spectrum("normalizeTo0dB",1,"fignum",250,"displayname","Rx Spectrum");
+
+    Duobinary().encode(tx_symbols).spectrum("normalizeTo0dB",1,"fignum",250,"displayname","DB encoded reference");
+
+    showEQNoisePSD(eq_noise,"fignum",250,"displayname",'Duobinary Target Noise after Equalization');
+
+    fprintf('DB tgt BER: %.2e \n',ber);
+
+
+end
 
 
 end

Functions/EQ_structures/vnle.m

@@ -22,6 +22,8 @@ function [eq_package] = vnle(eq_,M,rx_signal,tx_symbols,tx_bits,options)
         tx_bits 
         options.precode_mode db_mode
         options.showAnalysis = 0
+        options.eth_style = 0;
+        options.postFFE = []; 
     end
 
     %FFE or VNLE
@@ -31,6 +33,10 @@ function [eq_package] = vnle(eq_,M,rx_signal,tx_symbols,tx_bits,options)
     end
     [eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
 
+    if ~isempty(options.postFFE)
+        [eq_signal_sd,eq_noise] = options.postFFE.process(eq_signal_sd,tx_symbols);
+    end
+
     eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
 
     % precoding to mitigate error propagation, most prominently used in
@@ -50,7 +56,7 @@ function [eq_package] = vnle(eq_,M,rx_signal,tx_symbols,tx_bits,options)
         tx_symbols_precoded = Duobinary().encode(tx_symbols);
         tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
 
-        tx_bits = PAMmapper(M,0).demap(tx_symbols_precoded);
+        tx_bits = PAMmapper(M,0,"eth_style",options.eth_style).demap(tx_symbols_precoded);
 
         case db_mode.db_discard
 
@@ -68,26 +74,56 @@ function [eq_package] = vnle(eq_,M,rx_signal,tx_symbols,tx_bits,options)
 
     end
 
-    rx_bits = PAMmapper(M,0).demap(eq_signal_hd);
+    rx_bits = PAMmapper(M,0,"eth_style",options.eth_style).demap(eq_signal_hd);
 
     [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
     [evm_total,evm_lvl] = calc_evm(eq_signal_sd,tx_symbols);
     [inf_rate] = calc_air(eq_signal_sd,tx_symbols,"skip_front",10000,"skip_end",10000);
 
+
     eq_package.ber_vnle     = ber;
     eq_package.evm_total    = evm_total;
     eq_package.evm_lvl      = evm_lvl;
     eq_package.inf_rate_vnle = inf_rate;
-
     eq_package.snr = snr(eq_signal_sd.signal,eq_noise.signal);
 
+    eq_package.signal = eq_signal_sd;
+
+
     if options.showAnalysis
 
-        snr(eq_signal_sd.signal,eq_noise.signal);
+        fprintf('SNR: %d dB \n',snr(eq_signal_sd.signal,eq_noise.signal));
+
+        if M == 6
+            logm = 2.5;
+        else 
+            logm = log2(M);
+        end
+
+        fprintf('NGMI: %.4f \n', inf_rate/logm);
+
         fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
 
         fprintf('VNLE BER: %.2e \n',ber);
 
+        disp("%%%%%%%%%%%%%%%%%%%%%")
+
+        % showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients');
+        % 
+        % if ~isempty(options.postFFE)
+        %     showEQcoefficients('n1',options.postFFE.e,"displayname",'Coefficients');
+        % end
+        % 
+        % showEQNoisePSD(eq_noise);
+        % 
+        % showEQfilter(eq_.e,eq_signal_sd.fs.*2)
+
+        % noiselessness(tx_symbols,eq_noise,"displayname",'SNR after VNLE','fignum',301);
+
+        % showLevelHistogram(eq_signal_sd,tx_symbols,"fignum",302);
+
+       
+        
     end
 
 end

Functions/EQ_structures/vnle_postfilter_mlse.m

@@ -10,116 +10,258 @@ arguments
     tx_bits
     options.precode_mode db_mode
     options.showAnalysis = 0;
+    options.eth_style_symbol_mapping = 0;
+    options.postFFE = [];
+    options.database = [];
 end
 
-    %FFE or VNLE
-    [eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
+%FFE or VNLE
+[eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
 
-    eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
+if ~isempty(options.postFFE)
+    [eq_signal_sd,eq_noise] = options.postFFE.process(eq_signal_sd,tx_symbols);
+end
 
-    mlse_sig_sd = pf_.process(eq_signal_sd,eq_noise);
+eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
 
-    mlse_.DIR = pf_.coefficients;
-    % [mlse_sig_hd,mlse_sig_sd] = mlse_.process(mlse_sig_sd,tx_symbols);
-    mlse_sig_sd = mlse_.process(mlse_sig_sd);
+mlse_sig_sd = pf_.process(eq_signal_sd,eq_noise);
 
-    mlse_sig_hd = PAMmapper(M,0).quantize(mlse_sig_sd);
+mlse_.DIR = pf_.coefficients;
+% [mlse_sig_hd,mlse_sig_sd] = mlse_.process(mlse_sig_sd,tx_symbols);
+mlse_sig_sd = mlse_.process(mlse_sig_sd);
 
-    % precoding to mitigate error propagation, most prominently used in
-    % combination with duobinary signaling to avoid catastrophic error
-    % behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
+mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
 
-    % takes: 
-    %   -> M 
-    %   -> eq_signal_hd: hard decision signal after eq
-    %   -> tx_symbols:   that where used as reference for eq 
+% precoding to mitigate error propagation, most prominently used in
+% combination with duobinary signaling to avoid catastrophic error
+% behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
 
-    switch options.precode_mode
-        case db_mode.db_emulate
-        % re
-        eq_signal_hd = Duobinary().encode(eq_signal_hd,"M",M);
-        eq_signal_hd = Duobinary().decode(eq_signal_hd,"M",M);
+switch options.precode_mode
 
-        mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
-        mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
+    case db_mode.no_db
+        % TX Data is not precoded:
+
+        % A) Emulate diff precoding
+        eq_signal_hd_precoded = Duobinary().encode(eq_signal_hd,"M",M);
+        eq_signal_hd_precoded = Duobinary().decode(eq_signal_hd_precoded,"M",M);
+
+        mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
+        mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
 
         tx_symbols_precoded = Duobinary().encode(tx_symbols);
         tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
 
-        tx_bits = PAMmapper(M,0).demap(tx_symbols_precoded);
+        tx_bits_precoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
 
-        case db_mode.db_discard
+        rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd_precoded);
+        [~,errors_vnle_diff_precoded,ber_vnle_diff_precoded,~]   = calc_ber(rx_bits_vnle.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        % normal dsp for precoded sequence == discard/omit/ignore precode
-        tx_bits = PAMmapper(M,0).demap(tx_symbols);
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_precoded);
+        [~,errors_mlse_diff_precoded,ber_mlse_diff_precoded,~]  = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        case db_mode.db_encoded
+        %B) Just determine BER
+        rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd);
+        [bits_vnle,errors_vnle,ber_vnle,~]   = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        % normal DB encoded data (only for 10KM)
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
+        [bits_mlse,errors_mlse,ber_mlse,~]  = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-        case db_mode.db_precoded
+    case db_mode.db_precoded
 
-        eq_signal_hd = Duobinary().encode(eq_signal_hd,"M",M);
-        eq_signal_hd = Duobinary().decode(eq_signal_hd,"M",M);
+        % Daten SIND TATSÄCHLICH precoded auf TX Seite:
 
-        mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
-        mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
+        % A) Decode at Rx if no DB targeting was applied (we are in VNLE or MLSE EQ structure here!
+        eq_signal_hd_decoded = Duobinary().encode(eq_signal_hd,"M",M);
+        eq_signal_hd_decoded = Duobinary().decode(eq_signal_hd_decoded,"M",M);
+        rx_bits_vnle_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd_decoded);
+        [~,errors_vnle_diff_precoded,ber_vnle_diff_precoded,~]   = calc_ber(rx_bits_vnle_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-    end
+        mlse_sig_hd_decoded = Duobinary().encode(mlse_sig_hd,"M",M);
+        mlse_sig_hd_decoded = Duobinary().decode(mlse_sig_hd_decoded,"M",M);
+        rx_bits_mlse_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_decoded);
+        [~,errors_mlse_diff_precoded,ber_mlse_diff_precoded,~]  = calc_ber(rx_bits_mlse_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-    % METRICS OF VNLE %
-    rx_bits_vnle = PAMmapper(M,0).demap(eq_signal_hd);
-    [~,~,ber_vnle,~] = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+        % B) Omit the Coding by comparing with demapped TX symbol sequence
 
-    % correct TUM implementation of AIR
-    [inf_rate_vnle] = calc_air(eq_signal_sd,tx_symbols,"skip_front",10000,"skip_end",10000);
-    [evm_vnle_total,evm_vnle_lvl] = calc_evm(eq_signal_sd,tx_symbols);
+        tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols);
+        rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd);
+        [bits_vnle,errors_vnle,ber_vnle,~]   = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
-    % METRICS OF MLSE (HD-VITERBI)
-    rx_bits_mlse = PAMmapper(M,0).demap(mlse_sig_hd);
-    [~,~,ber_mlse,~] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
-
-
-    eq_package.ber_mlse = ber_mlse;
-    eq_package.ber_vnle = ber_vnle;
-    eq_package.evm_vnle_total = evm_vnle_total;
-    eq_package.evm_vnle_lvl = evm_vnle_lvl;
-    eq_package.air = inf_rate_vnle;
-
-    eq_package.eq = eq_;
-    eq_package.pf = pf_;
-    eq_package.mlse = mlse_;
-
-
-    if options.showAnalysis
-
-        % fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
-
-        fprintf('VNLE BER: %.2e \n',ber_vnle);
-
-        fprintf('MLSE BER: %.2e \n',ber_mlse);
-
-        showEQNoisePSD(eq_noise,"fignum",336,"displayname",'VNLE+DFE','postfilter_taps',pf_.coefficients);
-       
-
-        rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
-
-        tx_symbols.spectrum("normalizeTo0dB",1,"fignum",337,'displayname','Tx Signal');
-
-        showLevelHistogram(eq_signal_sd,tx_symbols)
-        % showLevelHistogram(mlse_sig_sd,tx_symbols)
-
-        showEQcoefficients(eq_.e,eq_.e2,eq_.e3,"displayname",'Coefficients');
-
-        showEQNoiseSNR(tx_symbols,eq_noise,"displayname",'vnle snr','fignum',101);
-
-        %%% EQ SNR Spectrum %230
-        %snr
-        snr_vnle = snr(tx_symbols.signal,eq_noise.signal);
-
-        % showErrorBurstCount(eq_signal_sd,tx_symbols)
-        
-
-    end
+        rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
+        [bits_mlse,errors_mlse,ber_mlse,~]  = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+
+end
+
+% METRICS OF VNLE SD Signal:
+[snr_vnle,snr_vnle_lvl]                             = calc_snr(tx_symbols.signal,eq_noise.signal);
+[gmi_vnle]                                          = calc_air(eq_signal_sd,tx_symbols,"skip_front",10000,"skip_end",10000);
+air_vnle                                            = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi_vnle ./ log2(double(M));
+[evm_vnle_total,evm_vnle_lvl]                       = calc_evm(eq_signal_sd,tx_symbols);
+
+% METRICS OF MLSE (HD-VITERBI)
+pf_.ncoeff = 1;
+pf_.process(eq_signal_sd,eq_noise);
+alpha = pf_.coefficients(2);
+
+eq_package.ber_mlse = ber_mlse;
+eq_package.ber_vnle = ber_vnle;
+eq_package.evm_vnle_total = evm_vnle_total;
+eq_package.evm_vnle_lvl = evm_vnle_lvl;
+eq_package.gmi = gmi_vnle;
+
+eq_package.eq = eq_;
+eq_package.pf = pf_;
+eq_package.mlse = mlse_;
+
+resultsVNLE = struct( ...
+    'result_id',    NaN, ...  %
+    'run_id',       NaN, ...  % Beispielhafte Run-ID
+    'eqParam_id',   NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
+    'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
+    'BER',          ber_vnle, ... % BER = 120 / 1.000.000
+    'numBits',      bits_vnle, ... % Beispiel: 1.000.000 Bits
+    'numBitErr',    errors_vnle, ... % Beispiel: 120 Bitfehler
+    'BER_precoded', ber_vnle_diff_precoded, ... % BER = 120 / 1.000.000
+    'numBitErr_precoded', errors_vnle_diff_precoded, ... % Beispiel: 120 Bitfehler
+    'SNR',          snr_vnle, ... % Beispielhafte SNR
+    'SNR_level',    jsonencode(snr_vnle_lvl), ... % SNR-Level als JSON-codiertes Array
+    'GMI',          gmi_vnle, ... % Beispielhafter GMI-Wert
+    'AIR',          air_vnle, ... % Beispielhafter AIR-Wert
+    'EVM',          evm_vnle_total, ... % Beispielhafte EVM
+    'EVM_level',    jsonencode(evm_vnle_lvl), ... % EVM-Level als JSON-codiertes Array
+    'Alpha',        [] ... % Beispielhafter Alpha-Wert
+    );
+
+if ~isempty(options.postFFE)
+    npostFFE = options.postFFE.order;
+else
+    npostFFE = 0;
+end
+
+equalizerConfigVNLE = struct( ...
+    'eq_id',        NaN, ...  % Auto-Inkrement, wird in der DB gesetzt
+    'equalizer_structure', int32(equalizer_structure.vnle), ...  % Beispiel: 1 (z.B. für vnle)
+    'M',            M, ...  % Ordnung der PAM-Konstellation
+    'target_constellation', jsonencode(round(unique(tx_symbols.signal),5)), ...  % Beispielhafter Target-String
+    'db_target',    0, ...  % 0 oder 1
+    'diff_precode',  int32(options.precode_mode), ...  % 0 oder 1
+    'postFFE',      ~isempty(options.postFFE), ...  % Beispielwert
+    'NpostFFE',     npostFFE, ...  % Beispielwert
+    'Ne1',          eq_.Ne(1), ...  % Feedforward Koeffizienten 1. Ordnung
+    'Ne2',          eq_.Ne(2), ...   % Feedforward Koeffizienten 2. Ordnung
+    'Ne3',          eq_.Ne(3), ...   % Feedforward Koeffizienten 3. Ordnung
+    'Nb1',          eq_.Nb(1), ...   % Decision Feedback Koeffizienten 1. Ordnung
+    'Nb2',          eq_.Nb(2), ...   % Decision Feedback Koeffizienten 2. Ordnung
+    'Nb3',          eq_.Nb(3), ...   % Decision Feedback Koeffizienten 3. Ordnung
+    'K',            eq_.K, ...     % Samples pro Symbol
+    'DCmu',         eq_.DCmu, ...  % Anpassungsrate für DC-Tap
+    'ideal_dfe',    eq_.ideal_dfe, ... % Flag für ideal DFE (0 oder 1)
+    'training_length', eq_.training_length, ...  % Anzahl Trainingssymbole
+    'training_loops', eq_.training_loops, ...  % Anzahl Trainingsdurchläufe
+    'TRmu1',        eq_.FFEmu, ...  % mu für DD-Modus (1. Ordnung)
+    'TRmu2',        eq_.FFEmu, ...  % mu für DD-Modus (2. Ordnung)
+    'TRmu3',        eq_.FFEmu, ...  % mu für DD-Modus (3. Ordnung)
+    'TRmuDFE',      eq_.DFEmu, ... % mu für DFE-Modus im DD
+    'dd_loops',     5, ...  % Anzahl Durchläufe im DD-Modus
+    'DDmu1',        eq_.DDmu(1), ...  % mu für DD-Modus (1. Ordnung)
+    'DDmu2',        eq_.DDmu(2), ...  % mu für DD-Modus (2. Ordnung)
+    'DDmu3',        eq_.DDmu(3), ...  % mu für DD-Modus (3. Ordnung)
+    'DDmuDFE',      eq_.DDmu(4), ... % mu für DFE-Modus im DD
+    'comment',      'function: vnle_postfilter_mlse', ...  % Zusätzliche Kommentare
+    'config_hash',  NaN ...
+    );
+
+
+resultsMLSE = struct( ...
+    'result_id',    NaN, ...  %
+    'run_id',       NaN, ...  % Beispielhafte Run-ID
+    'eqParam_id',   NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
+    'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
+    'BER',          ber_mlse, ... % BER = 120 / 1.000.000
+    'numBits',      bits_mlse, ... % Beispiel: 1.000.000 Bits
+    'numBitErr',    errors_mlse, ... % Beispiel: 120 Bitfehler
+    'BER_precoded', ber_mlse_diff_precoded, ... % BER = 120 / 1.000.000
+    'numBitErr_precoded', errors_mlse_diff_precoded, ... % Beispiel: 120 Bitfehler
+    'SNR',          [], ... % Beispielhafte SNR
+    'SNR_level',    jsonencode([]), ... % SNR-Level als JSON-codiertes Array
+    'GMI',          [], ... % Beispielhafter GMI-Wert
+    'AIR',          [], ... % Beispielhafter AIR-Wert
+    'EVM',          [], ... % Beispielhafte EVM
+    'EVM_level',    jsonencode([]), ... % EVM-Level als JSON-codiertes Array
+    'Alpha',        alpha, ... % Beispielhafter Alpha-Wert
+    'MLSE_dir', jsonencode([mlse_.DIR])...
+    );
+
+
+equalizerConfigMLSE = struct( ...
+    'eq_id',        NaN, ...  % Auto-Inkrement, wird in der DB gesetzt
+    'equalizer_structure', int32(equalizer_structure.vnle_pf_mlse), ...  % Beispiel: 1 (z.B. für vnle)
+    'M',            M, ...  % Ordnung der PAM-Konstellation
+    'target_constellation', jsonencode(round(unique(tx_symbols.signal),5)), ...  % Beispielhafter Target-String
+    'db_target',    0, ...  % 0 oder 1
+    'diff_precode',  int32(options.precode_mode), ...  % 0 oder 1
+    'postFFE',      ~isempty(options.postFFE), ...  % Beispielwert
+    'NpostFFE',     npostFFE, ...  % Beispielwert
+    'Ne1',          eq_.Ne(1), ...  % Feedforward Koeffizienten 1. Ordnung
+    'Ne2',          eq_.Ne(2), ...   % Feedforward Koeffizienten 2. Ordnung
+    'Ne3',          eq_.Ne(3), ...   % Feedforward Koeffizienten 3. Ordnung
+    'Nb1',          eq_.Nb(1), ...   % Decision Feedback Koeffizienten 1. Ordnung
+    'Nb2',          eq_.Nb(2), ...   % Decision Feedback Koeffizienten 2. Ordnung
+    'Nb3',          eq_.Nb(3), ...   % Decision Feedback Koeffizienten 3. Ordnung
+    'K',            eq_.K, ...     % Samples pro Symbol
+    'DCmu',         eq_.DCmu, ...  % Anpassungsrate für DC-Tap
+    'ideal_dfe',    eq_.ideal_dfe, ... % Flag für ideal DFE (0 oder 1)
+    'training_length', eq_.training_length, ...  % Anzahl Trainingssymbole
+    'training_loops', eq_.training_loops, ...  % Anzahl Trainingsdurchläufe
+    'TRmu1',        eq_.FFEmu, ...  % mu für DD-Modus (1. Ordnung)
+    'TRmu2',        eq_.FFEmu, ...  % mu für DD-Modus (2. Ordnung)
+    'TRmu3',        eq_.FFEmu, ...  % mu für DD-Modus (3. Ordnung)
+    'TRmuDFE',      eq_.DFEmu, ... % mu für DFE-Modus im DD
+    'dd_loops',     5, ...  % Anzahl Durchläufe im DD-Modus
+    'DDmu1',        eq_.DDmu(1), ...  % mu für DD-Modus (1. Ordnung)
+    'DDmu2',        eq_.DDmu(2), ...  % mu für DD-Modus (2. Ordnung)
+    'DDmu3',        eq_.DDmu(3), ...  % mu für DD-Modus (3. Ordnung)
+    'DDmuDFE',      eq_.DDmu(4), ... % mu für DFE-Modus im DD
+    'MLSE_mode',    'viterbi', ...  % Beispiel: MLSE-Modus als String
+    'MLSE_trellis_states', jsonencode(mlse_.trellis_states), ...  % Trellis-States, z.B. als JSON-String oder kommasepariert
+    'comment',      'function: vnle_postfilter_mlse', ...  % Zusätzliche Kommentare
+    'config_hash',  NaN ...
+    );
+eq_package.resultsVNLE = resultsVNLE;
+eq_package.resultsMLSE = resultsMLSE;
+eq_package.equalizerConfigVNLE = equalizerConfigVNLE;
+eq_package.equalizerConfigMLSE = equalizerConfigMLSE;
+
+% eq_package.vnle_out = eq_signal_sd;
+if options.showAnalysis
+
+    % fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
+
+    fprintf('VNLE BER: %.2e \n',ber_vnle);
+
+    fprintf('MLSE BER: %.2e \n',ber_mlse);
+
+    showEQNoisePSD(eq_noise,"fignum",336,"displayname",'Residual Noise after VNLE','postfilter_taps',pf_.coefficients);
+
+
+    rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
+
+    tx_symbols.spectrum("normalizeTo0dB",1,"fignum",337,'displayname','Tx Signal');
+
+    showLevelHistogram(eq_signal_sd,tx_symbols)
+    % showLevelHistogram(mlse_sig_sd,tx_symbols)
+
+    showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients');
+
+    showEQNoiseSNR(tx_symbols,eq_noise,"displayname",'vnle snr','fignum',101);
+
+    %%% EQ SNR Spectrum %230
+    %snr
+
+
+    % showErrorBurstCount(eq_signal_sd,tx_symbols)
+
+
+end
 
 end

Functions/EQ_visuals/showEQNoiseSNR.m

@@ -1,7 +1,7 @@
-function showEQNoiseSNR(tx_signal, rx_signal, options)
+function showEQNoiseSNR(eq_signal, noise_signal, options)
 arguments
-    tx_signal
-    rx_signal 
+    eq_signal
+    noise_signal 
     options.fs_tx
     options.fs_rx
     options.fignum (1,1) double = NaN % Default to NaN if not provided
@@ -16,13 +16,13 @@ end
         fig = figure(options.fignum); % Use the specified figure number
     end
 
-    if isa(tx_signal,'Signal')
-        options.fs_tx = tx_signal.fs;
-        tx_signal = tx_signal.signal;
+    if isa(eq_signal,'Signal')
+        options.fs_tx = eq_signal.fs;
+        eq_signal = eq_signal.signal;
     end
-    if isa(rx_signal,'Signal')
-        options.fs_rx = rx_signal.fs;
-        rx_signal = rx_signal.signal;
+    if isa(noise_signal,'Signal')
+        options.fs_rx = noise_signal.fs;
+        noise_signal = noise_signal.signal;
     end
 
 
@@ -37,10 +37,10 @@ end
     % Ensure the figure is ready before calling spectrum
     title('SNR of received Signal')
 
-    fft_length = 2^(nextpow2(length(tx_signal))-7);
+    fft_length = 2^(nextpow2(length(eq_signal))-7);
     
-    [s_lin,w] = pwelch(tx_signal,hanning(fft_length),fft_length/2,fft_length,options.fs_tx,"centered","psd","mean");
-    [n_lin,w] = pwelch(rx_signal,hanning(fft_length),fft_length/2,fft_length,options.fs_rx,"centered","psd","mean");
+    [s_lin,w] = pwelch(eq_signal,hanning(fft_length),fft_length/2,fft_length,options.fs_tx,"centered","psd","mean");
+    [n_lin,w] = pwelch(noise_signal,hanning(fft_length),fft_length/2,fft_length,options.fs_rx,"centered","psd","mean");
 
     w = w.*1e-9;
     snr_dbm = 10*log10(s_lin./n_lin);
@@ -48,6 +48,7 @@ end
     % figure(231)
     hold on
     plot(w,snr_dbm,'DisplayName','SNR','LineWidth',0.5,'Color',options.color);
+    yline(mean(snr_dbm),'HandleVisibility','off','Color',options.color);
     xlabel("Frequency in GHz");
 
     edgetick = 2^(nextpow2(options.fs_tx*1e-9));

Functions/EQ_visuals/showEQcoefficients.m

@@ -1,58 +1,67 @@
-function showEQcoefficients(n1, n2, n3, options)
-    % Show filter coefficients as stem plot
-    % n1, n2, and n3 in different subplots
-    % Scale all y-axis to -1 and 1
+function showEQcoefficients(options)
+    % Show filter coefficients as stem plots.
+    % Only the provided coefficient arrays (n1, n2, n3) are shown,
+    % each in its own subplot. The y-axis is scaled to [-1, 1].
 
     arguments
-        n1
-        n2
-        n3
-        options.fignum (1,1) double = NaN % Default to NaN if not provided
-        options.displayname (1,:) char = '' % Default to an empty string if not provided
+        options.n1 = [];
+        options.n2 = [];
+        options.n3 = [];
+        options.fignum (1,1) double = NaN; % Default: create new figure if NaN
+        options.displayname (1,:) char = ''; % Default: empty string
         options.color = [0.2157, 0.4941, 0.7216];
-        options.clf = 0; % Clear figure before plotting new
+        options.clf = 0; % Clear figure before plotting if set to 1
     end
 
-    % Determine the figure number to use or create a new figure
+    % Determine the figure number to use or create a new one.
     if isnan(options.fignum)
-        fig = figure; % Create a new figure and get its handle
+        fig = figure; 
     else
-        fig = figure(options.fignum); % Use the specified figure number
+        fig = figure(options.fignum);
     end
 
     if options.clf
-        clf(fig); % Clear the figure if requested
+        clf(fig);
     end
 
     hold on
     ax = gca;
     N = numel(ax.Children);
 
-    % Set up a colormap for consistent coloring
+    % Set up a colormap for consistent coloring.
     cmap = linspecer(8);
     options.color = cmap(mod(N, size(cmap, 1)) + 1, :);
 
-    % Create subplots for n1, n2, n3
-    for i = 1:3
-        subplot(3, 1, i);
-        switch i
-            case 1
-                stem(n1, 'Color', options.color, 'LineWidth', 1,'Marker','.','MarkerSize',10);
-                title(sprintf('1st order Filter Coefficients: %d',numel(n1)));
-            case 2
-                stem(n2, 'Color', options.color, 'LineWidth', 1,'Marker','.','MarkerSize',10);
-                title(sprintf('2nd order Filter Coefficients: %d',numel(n2)));
-            case 3
-                stem(n3, 'Color', options.color, 'LineWidth', 1,'Marker','.','MarkerSize',10);
-                title(sprintf('3rd order Filter Coefficients: %d',numel(n3)));
-        end
-        ylim([-1, 1]); % Scale y-axis to -1 and 1
+    % Build cell arrays for coefficients and their corresponding titles.
+    coeffs = {};
+    titles = {};
+
+    if ~isempty(options.n1)
+        coeffs{end+1} = options.n1;
+        titles{end+1} = sprintf('1st order Filter Coefficients: %d', numel(options.n1));
+    end
+    if ~isempty(options.n2)
+        coeffs{end+1} = options.n2;
+        titles{end+1} = sprintf('2nd order Filter Coefficients: %d', numel(options.n2));
+    end
+    if ~isempty(options.n3)
+        coeffs{end+1} = options.n3;
+        titles{end+1} = sprintf('3rd order Filter Coefficients: %d', numel(options.n3));
+    end
+
+    numSubplots = numel(coeffs);
+
+    for i = 1:numSubplots
+        subplot(1, numSubplots, i);
+        stem(coeffs{i}, 'Color', options.color, 'LineWidth', 1, ...
+             'Marker', '.', 'MarkerSize', 10);
+        title(titles{i});
+        ylim([-1, 1]); % Set y-axis limits to [-1, 1]
         grid on;
-        grid minor
+        grid minor;
         xlabel('Coefficient Index');
         ylabel('Amplitude');
     end
 
-    % Ensure the layout is tight for better visibility
-    sgtitle('Filter Coefficients'); % Overall title
+    sgtitle('Filter Coefficients'); % Overall title for the figure
 end

Functions/EQ_visuals/showEQfilter.m

@@ -0,0 +1,36 @@
+
+function showEQfilter(coefficients,fs)
+
+    % Assuming that obj.e contains the final FFE filter coefficients.
+    % Set the number of frequency points and sampling frequency.
+    nfft = 1024;  % Number of frequency points
+    
+    % Compute the frequency response of the FFE filter.
+    [H, f] = freqz(coefficients, 1, nfft, fs);
+    
+    % Keep only the first half of the frequency response (up to the Nyquist frequency).
+    half_nfft = floor(nfft/2) + 1;
+    f = f(1:half_nfft);
+    H = H(1:half_nfft);
+    
+    % Plot the magnitude and phase responses.
+    figure;
+    
+    % Magnitude response (in dB)
+    subplot(2,1,1);
+    hold on
+    plot(f.*1e-9, 20*log10(abs(1./H)));
+    title('(Inverted) Magnitude Response of FFE Filter');
+    xlabel('Frequency (Hz)');
+    ylabel('Magnitude (dB)');
+    grid on;
+    
+    % Phase response
+    subplot(2,1,2);
+    plot(f.*1e-9, unwrap(angle(H)));
+    title('Phase Response of FFE Filter');
+    xlabel('Frequency (Hz)');
+    ylabel('Phase');
+    grid on;
+
+end

Functions/EQ_visuals/showLevelHistogram.m

@@ -39,7 +39,9 @@ end
         intermediate = received_sd(lvl,:);
         cnt(lvl) = round(numel(intermediate(~isnan(intermediate)))./length(eq_signal),3).*100;
         hold on
+        warning off
         histogram(received_sd(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' | ',num2str(cnt(lvl)),' %'],'FaceColor',lvlcol(lvl,:),'Normalization','pdf');
+        warning on
     end
     legend
     grid on

Functions/Lab_helper/loadFreqResp.m

@@ -0,0 +1,9 @@
+
+precomp_path = "D:\kiel_dsp\imdd_simulation\projects\HighSpeed_ETH";
+precomp_filename = "lab_high_speed_nachtschichtmzm";
+% precomp_filename = "lab_high_speed";
+% precomp_filename = "lab_high_speed";
+
+freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
+freqresp.load('loadPath',precomp_path,'fileName',precomp_filename);
+freqresp.plot();

Functions/Metrics/calc_air_plain.m

@@ -0,0 +1,40 @@
+function [airs] = calc_air_plain(noisy_signal,reference_signal,options)
+    % Calculation of AIR acc. to J. Kozesnik, „Numerically Computing Achievable Rates of  Memoryless Channels“, Francisco Javier Garcıa-Gomez,  doi: 10.1007/978-94-009-9857-5.
+    % Implementation is not accessible, I mailed TUM to get the code...
+
+    arguments(Input)
+        noisy_signal;
+        reference_signal;
+        options.skip_front = 0;
+        options.skip_end = 0;
+        options.returnErrorLocation = 0;
+    end
+    
+    options.skip_end = abs(options.skip_end);
+    options.skip_front = abs(options.skip_front);
+    
+    assert((options.skip_end+options.skip_front)<length(noisy_signal),"You can not skip more bits than overall length of data! Set skip_front or skip_end to lower value or check data_in");
+    
+    % TRIM
+    [noisy_signal,reference_signal]=trimseq(noisy_signal,reference_signal,options.skip_front,options.skip_end);
+    
+    % CALC EVM
+    %%% new implementation of AIR
+    constellation = unique(reference_signal);
+    reference_idx = arrayfun(@(x) find(constellation == x, 1), reference_signal);
+    air = air_garcia_implementation(constellation',noisy_signal',reference_idx');
+    
+    
+    function [data_,reference_]=trimseq(data,reference,skipstart,skip_end)
+    
+        data_  =  data(skipstart+1:end-skip_end,:);
+        
+        delta_bits = length(reference) - length(data);
+        
+        skip_end = delta_bits + skip_end;
+        
+        reference_ = reference(skipstart+1:end-skip_end,:);
+    
+    end
+
+end

Functions/Metrics/calc_snr.m

@@ -0,0 +1,36 @@
+function [snr_all, snr_per_level] = calc_snr(tx_signal, eq_noise)
+% CALC_SNR Calculates overall SNR and level-wise SNR for a PAM-M constellation.
+%
+%   [snr_all, snr_per_level] = calc_snr(tx_signal, eq_noise)
+%
+%   Inputs:
+%       tx_signal - Vector of transmitted signal values.
+%       eq_noise  - Vector of corresponding noise samples.
+%
+%   Outputs:
+%       snr_all       - Overall SNR computed using all signal values.
+%       snr_per_level - A vector where each element is the SNR computed
+%                       for a unique amplitude level in tx_signal.
+%
+%   The function first computes the overall SNR using the full signal vectors.
+%   Then it uses the unique levels in tx_signal to calculate the SNR for
+%   the symbols corresponding to each level separately.
+
+    % Calculate overall SNR using the complete signals
+    snr_all = snr(tx_signal, eq_noise);
+
+    % Get the unique amplitude levels in the transmitted signal
+    levels = unique(tx_signal);
+    
+    % Preallocate an array to store the SNR for each unique level
+    snr_per_level = zeros(size(levels));
+    
+    % Loop over each unique level to compute the SNR for that level
+    for i = 1:length(levels)
+        % Find indices where tx_signal equals the current level
+        idx = (tx_signal == levels(i));
+        
+        % Compute the SNR for these indices
+        snr_per_level(i) = snr(tx_signal(idx), eq_noise(idx));
+    end
+end

Functions/Theory/modifiedGodardTimingRecovery.m

@@ -0,0 +1,62 @@
+function tau_error = modifiedGodardTimingRecovery(rx, N, eta, beta)
+% modifiedGodardTimingRecovery
+%
+% This function estimates the symbol timing error using the modified Godard
+% approach in the frequency domain as described in:
+%
+% "Modified Godard Timing Recovery for Non-Integer Oversampling Receivers"
+% Appl. Sci. 2017, 7, 655. :contentReference[oaicite:0]{index=0}​:contentReference[oaicite:1]{index=1}
+%
+% Inputs:
+%   rx   - Received time-domain signal (vector)
+%   N    - FFT size (should be an even integer)
+%   eta  - Effective oversampling factor used for timing recovery (eta > 1)
+%   beta - Roll-off related parameter (0 < beta <= 1)
+%
+% Output:
+%   tau_error - Estimated timing error (in sample units)
+%
+% Implementation Notes:
+%   1. The function computes an N-point FFT of the first N samples of rx.
+%   2. It then determines an offset (Delta) defined as:
+%          offset = round((1 - 1/eta) * N)
+%   3. To avoid index overflow, the summation is taken over indices k from 1 to
+%      floor(N/2) - offset.
+%   4. The timing error is estimated as:
+%          tau_error = ( (1+beta)/(2*eta*N - 1) * sum(phase difference) ) / (2*pi)
+%      where the phase difference is (angle(R(k)) - angle(R(k+offset)))
+%
+% Make sure that the input signal rx contains at least N samples.
+
+% Check input length
+if length(rx) < N
+    error('Input signal length must be at least N.');
+end
+
+% Compute the N-point FFT of the first N samples of rx
+R = fft(rx(1:N), N);
+
+% Determine the offset based on the oversampling factor (eta)
+offset = round((1 - 1/eta) * N);
+
+% Define the summation range to avoid index overflow
+k_min = 1;
+k_max = floor(N/2) - offset;
+if k_max < k_min
+    error('Chosen parameters result in an empty summation range. Adjust N, eta, or beta.');
+end
+
+% Compute the sum of phase differences over the selected frequency bins
+phase_diff_sum = 0;
+for k = k_min:k_max
+    phase_k = angle(R(k));
+    phase_k_offset = angle(R(k + offset));
+    phase_diff_sum = phase_diff_sum + (phase_k - phase_k_offset);
+end
+
+% Normalization factor as per the modified Godard algorithm
+norm_factor = (1 + beta) / (2 * eta * N - 1);
+
+% Estimate the timing error in sample units
+tau_error = (norm_factor * phase_diff_sum) / (2 * pi);
+end

Functions/beautifyBERplot.m

@@ -9,7 +9,9 @@ function beautifyBERplot()
     for i = 1:length(lines)
         lines(i).LineWidth = 1.3;  % Thicker line width
         %lines(i).LineStyle = '-';  % Solid lines for simplicity
-        lines(i).Marker = markers{mod(i-1, num_markers) + 1}; % Assign markers cyclically
+        if string(lines(i).Marker) == "none"
+            lines(i).Marker = markers{mod(i-1, num_markers) + 1}; % Assign markers cyclically
+        end
         lines(i).MarkerSize = 4;   % Marker size
         lines(i).MarkerFaceColor = 'auto'; % Use line color for marker face
     end
@@ -23,7 +25,7 @@ function beautifyBERplot()
     
     % Set logarithmic scale for y-axis, but only if it makes sense.
     % If this is not always desired, you could condition this on the presence of lines or data.
-    % set(gca, 'YScale', 'log');
+    set(gca, 'YScale', 'log');
 
     % Customize grid and box appearance
     set(gca, 'Box', 'on', 'LineWidth', 0.8);  % Thicker border

Functions/moveit_wrapper_.m

@@ -0,0 +1,40 @@
+function [data_out, state_out] = moveit_wrapper(func_name, data_in, para)
+    % Generic wrapper for legacy MATLAB functions using loop-based execution
+    %
+    % Usage:
+    %   [data_out, state_out] = wrapper('quantize', data_in, para);
+    %
+    % Inputs:
+    %   - func_name: Name of the function as a string (e.g., 'quantize')
+    %   - data_in: Input signal or empty for initialization
+    %   - para: Structure with parameters (optional)
+    %
+    % Outputs:
+    %   - data_out: Processed output signal
+    %   - state_out: Internal state of the function
+    
+    global loop;
+
+    % Ensure the function exists
+    if ~exist(func_name, 'file')
+        error('Function "%s" does not exist.', func_name);
+    end
+
+    % Step 1: Get default parameters if not provided
+    if nargin < 3 || isempty(para)
+        loop = 0;  % Request parameter structure
+        [para, comment] = feval(func_name);
+    end
+
+    % Initialize state
+    state = struct();
+
+    % Step 2: Initialize the function
+    loop = 0;
+    [~, state_] = feval(func_name, data_in, state, para);
+
+    % Step 3: Process input signal
+    loop = 1;
+    [data_out, state_out] = feval(func_name, data_in, state_, para);
+    
+end

Functions/showTransferFunction.m

@@ -0,0 +1,22 @@
+
+function showTransferFunction(coeffs,options)
+
+arguments
+    coeffs 
+    options.fignum = 765
+    options.DisplayName = ''
+    options.color = [1 1 0.1]
+end
+% Define the filter taps
+    
+    [H, w] = freqz(coeffs, 1, 1024, 1);
+    
+    figure(options.fignum);
+    hold on
+    plot(w, 10*log10(abs(H)), 'LineWidth', 2,'DisplayName',options.DisplayName,'Color',options.color); %todo
+    xlabel('Normalized Frequency');
+    ylabel('Amplitude in dB');
+    grid on;
+    ylim([-20,10])
+
+end

projects/HighSpeedExperiment_2024/auswertung MPI/analyze_mpi.m

@@ -0,0 +1,92 @@
+
+% basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+if 1
+
+    uloops              = struct;
+    uloops.precomp      = [0,1];
+    uloops.db_precode   = [0,1];
+    uloops.bitrate      = [420].*1e9; %[300,330,360,390,420,450,480] [224,336,360,390,420,448] for MPI
+    % uloops.laser_wavelength = [1293,1297.5,1302,1306.5,1310,1313.4,1318,1322.7,1327.4];
+    uloops.laser_wavelength = [1310];
+    uloops.M            = [4];
+    uloops.link_length  = [1]; % 1,2,3,5,6,8,10
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    % wh = submit_simulations(wh,"parallel",0,"simulation_mode",0);
+    wh = submit_handle(@dsp_mpi,wh,"parallel",1);
+
+end
+
+a = wh_mpi_112gbd.getStoValue('ber',uloops.precomp, uloops.db_precode, uloops.bitrate(1) , uloops.laser_wavelength, uloops.M, uloops.link_length);
+
+%VNLE standalone
+try
+    ber_vnle = cellfun(@(x) x.vnle_dfe_package{1,1}.ber_vnle, a);
+end
+%MLSE
+try
+    ber_values_mlse = cellfun(@(s) cellfun(@(pkg) pkg.ber_mlse, s.vnle_pf_package, 'UniformOutput', false), a, 'UniformOutput', false);
+    ber_values_mlse =  cell2mat(ber_values_mlse{1});
+
+end
+%DB
+try
+    ber_values_db = cellfun(@(s) cellfun(@(pkg) pkg.ber, s.dbtgt_package, 'UniformOutput', false), a, 'UniformOutput', false);
+    ber_values_db =  cell2mat(ber_values_db{1});
+end
+
+xax = [0
+     3
+     6
+     9
+    12
+    15
+    18
+    21
+    24
+    27
+    30
+    45];
+cols = cbrewer2('Set1',8);
+
+% Compute min, max, and mean for PAM 4 MLSE
+min_mlse  = min(ber_values_mlse, [], 2);
+max_mlse  = max(ber_values_mlse, [], 2);
+mean_mlse = mean(ber_values_mlse, 2);
+err_lower_mlse = mean_mlse - min_mlse;
+err_upper_mlse = max_mlse - mean_mlse;
+err_mlse = [err_lower_mlse, err_upper_mlse];
+
+% Compute min, max, and mean for PAM 4 DB tgt.
+min_db  = min(ber_values_db, [], 2);
+max_db  = max(ber_values_db, [], 2);
+mean_db = mean(ber_values_db, 2);
+err_lower_db = mean_db - min_db;
+err_upper_db = max_db - mean_db;
+err_db = [err_lower_db, err_upper_db];
+
+figure(1)
+hold on
+title('MPI');
+
+% Plot the MLSE curve with bounded error using boundedline
+[hl_mlse, hp_mlse] = boundedline(xax, mean_mlse, err_mlse,'Color', cols(1,:));
+plot(xax,ber_values_mlse,'DisplayName','PAM 4 MLSE','Color',cols(1,:),'LineStyle','-','HandleVisibility','on','Marker','none','LineWidth',0.2);
+
+% Plot the DB tgt. curve with bounded error using boundedline
+[hl_db, hp_db] = boundedline(xax, mean_db, err_db, 'Color', cols(2,:));
+plot(xax,ber_values_db,'DisplayName','PAM 4 MLSE','Color',cols(2,:),'LineStyle','-','HandleVisibility','on','Marker','none','LineWidth',0.2);
+
+
+% Format the plot
+xticks(xax);
+set(gca, 'YScale', 'log');
+ylim([5e-5 0.4]);
+xlim([min(xax) max(xax)]);
+yline([4.85e-3, 2e-2], 'HandleVisibility', 'off');
+legend
+% beautifyBERplot()
+xlabel('Interference Attenuation');
+ylabel('BER');

projects/HighSpeedExperiment_2024/auswertung MPI/dsp_mpi.m

@@ -0,0 +1,333 @@
+function  [output] = dsp_mpi(varargin)
+
+simulation_mode = 0;
+
+%%% Change folder
+curFolder = pwd;
+funcFolder=fileparts(mfilename('fullpath'));
+if ~isempty(funcFolder)
+    cd(funcFolder);
+end
+
+%%% Run parameters
+% TX
+M               = 4;
+fsym            = 180e9;
+
+apply_pulsef    = 1;
+fdac            = 256e9;
+fadc            = 256e9;
+random_key      = 1;
+
+interference_attenuation = 0;
+is_mpi          = 1;
+
+precomp         = 0;
+db_precode      = 0;
+db_encode       = 0;
+
+rcalpha         = 0.05;
+kover           = 16;
+vbias_rel       = 0.5;
+u_pi            = 2.9;
+vbias           = -vbias_rel*u_pi;
+laser_wavelength    = 1293;
+laser_linewidth     = 0;
+tx_bw_nyquist   = 0.8;
+
+% Channel
+link_length     = 1;
+
+% RX
+rop = -5;
+rx_bw_nyquist = 0.8;
+
+vnle_order1 = 50;
+vnle_order2 = 5;
+vnle_order3 = 5;
+
+vnle_order=[vnle_order1,vnle_order2,vnle_order3];
+dfe_order = [0 0 0];
+
+pf_ncoeffs = 1;
+
+alpha = 0;
+
+len_tr  = 4096*2;
+
+mu_ffe1 = 0.0001;
+mu_ffe2 = 0.0008;
+mu_ffe3 = 0.001;
+mu_dc = 0.005;
+mu_dc = 0;
+
+mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
+mu_dfe = 0.0004;
+
+
+dfe_ = sum(dfe_order)>0;
+
+doub_mode = db_mode.no_db;
+
+%%% change specific parameter if given in varargin
+% Parse optional input arguments
+if ~isempty(varargin)
+    var_s = varargin{1};
+    if isstruct(var_s)
+        fields = fieldnames(var_s);
+        for i = 1:numel(fields)
+            if isnumeric(fields{i})
+                eval([fields{i}, ' = ',  num2str( var_s.(fields{i}) ), ';']);
+                fprintf("%s <-- %.2f \n", fields{i}, var_s.(fields{i}));
+            else
+                eval([fields{i}, ' = ',  'var_s.(fields{',num2str(i),'})' , ';']);
+            end
+
+        end
+    else
+        error('Optional variables should be passed as a struct.');
+    end
+end
+
+
+
+if doub_mode ~= db_mode.db_encoded
+    if precomp == 0 && db_precode == 1
+        doub_mode = db_mode.db_precoded;
+
+        db_precode      = 1; % preceded data (in my measurement set, this corresponds to low precomp too!)
+        discard_precode = 0; %
+        emulate_precode = 0;
+        legendentry = 'low precomp; precoded';
+        disp('low precomp; precoded')
+
+    elseif precomp == 1 && db_precode == 1
+        doub_mode = db_mode.db_emulate;
+
+        db_precode      = 0; % preceded data (in my measurement set, this corresponds to low precomp too!)
+        discard_precode = 0; %
+        emulate_precode = 1;
+        legendentry = 'high precomp; precoded';
+        disp('high precomp; precoded')
+
+    elseif precomp == 0 && db_precode == 0
+        doub_mode = db_mode.db_discard;
+
+        db_precode      = 1; % preceded data (in my measurement set, this corresponds to low precomp too!)
+        discard_precode = 1; %
+        emulate_precode = 0;
+        legendentry = 'no precomp; not precoded';
+        disp('no precomp; not precoded')
+
+    elseif precomp == 1 && db_precode == 0
+        doub_mode = db_mode.no_db;
+
+        db_precode      = 0; % preceded data (in my measurement set, this corresponds to low precomp too!)
+        discard_precode = 0; %
+        emulate_precode = 0;
+        legendentry = 'high precomp; not precoded';
+        disp('high precomp; not precoded')
+
+    end
+
+else
+
+end
+
+fsym_ = floor( bitrate*1e-9./log2(M) ).*1e9;
+
+if fsym_ ~= fsym
+    fsym = fsym_;
+    % fprintf('Adapted symbolrate to %d GBd, to match provided bitrate of %d GBit/s using PAM %d \n',fsym.*1e-9,bitrate.*1e-9, M);
+end
+f_nyquist       = fsym/2;
+
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+useGui = 0;
+% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+filterParams = database.tables;
+% filterParams.Runs.run_id = 2958; % no db
+% filterParams.Runs.run_id = 2937; % no db
+filterParams.Configurations = struct( ...
+    'bitrate',          bitrate, ...
+    'db_mode',          db_precode+db_encode, ...
+    'fiber_length',     link_length, ...
+    'interference_attenuation', [], ...
+    'interference_path_length', [], ...
+    'is_mpi',           is_mpi, ...
+    'pam_level',        M, ...
+    'precomp_amp',      [], ...
+    'rop_attenuation',  0, ...
+    'symbolrate',       [], ...
+    'v_awg',            [], ...
+    'v_bias',           [], ...
+    'wavelength',       laser_wavelength ...
+    );
+
+selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
+    'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','Measurements.power_rop','Configurations.v_bias',...
+    'Configurations.interference_attenuation'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+[~, uniqueIdx] = unique(dataTable.run_id);  % Get unique run_id indices
+dataTable = dataTable(uniqueIdx,:);  % Extract unique configurations for each run_id
+fprintf('Found %d entries for requested Configuration. IDs are: %s \n \n',size(dataTable,1),jsonencode(dataTable.run_id(1:min(size(dataTable,1),100))));
+
+
+output = struct();
+vnle_pf_package = {};
+vnle_dfe_package = {};
+dbtgt_package = {};
+
+disp(num2str(bitrate))
+
+for iatt = 1:numel(dataTable.interference_attenuation)
+    
+    current_run_id = dataTable.run_id(iatt);
+
+    Tx_bits     = load([basePath, char(dataTable.tx_bits_path(iatt))]);
+    Tx_bits     = Tx_bits.Bits;
+    Symbols_mapped = PAMmapper(M,0).map(Tx_bits);
+    Symbols_mapped.fs = fsym;
+
+    Symbols  = load([basePath, char(dataTable.tx_symbols_path(iatt))]);
+    Symbols  = Symbols.Symbols;
+
+    Scpe_load     = load([basePath, char(dataTable.rx_sync_path(iatt))]);
+    Scpe_cell     = Scpe_load.S;
+    [~,~,found]=Scpe_cell{2}.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",1);
+
+    if ~found
+        Raw_signal = load([basePath, char(dataTable.rx_raw_path(1))]);
+        Raw_signal = Raw_signal.Scpe_sig_raw;
+        [~,Scpe_cell,found] =Raw_signal.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",1);
+    end
+
+    if ~found
+        if length(Symbols_mapped.signal) == sum(Symbols_mapped.signal == Symbols.signal)
+            warning('Could not synchronize the received signal with the stored symbols!')
+        else
+            [~,Scpe_cell,found] =Raw_signal.tsynch("reference",Symbols_mapped,"fs_ref",fsym,"debug_plots",0);
+        end
+        if ~found
+            warning('Could not synchronize the received signal with the stored symbols!')
+        end
+    end
+    
+    fsym = Symbols.fs;
+
+    if db_precode
+        Symbols_precoded = Symbols;
+    end
+
+
+
+    proc_occ = min(15,length(Scpe_cell));
+    for occ = 1:proc_occ
+
+        Scpe_sig = Scpe_cell{occ};
+
+        %%%%%% Sample to 2x fsym %%%%%%
+        Scpe_sig =  Scpe_sig.resample("fs_out",2*fsym);
+
+        %%%%%% Sync Rx signal with reference %%%%%%
+        [Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
+
+        Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
+
+        Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
+
+
+        %%% EQUALIZING
+
+
+        % eq_mlse     = FFE_DCremoval("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0,"dc_buffer_len",1,"mu_dc",0.05);
+        % eq_mlse     = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0);
+        % eq_mlse     = FFE_DCremoval("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0,"dc_buffer_len",512,"mu_dc",0.05);
+
+        mu_ffe = [mu_ffe1 mu_ffe2 mu_ffe3];
+        vnle_order=[vnle_order1,vnle_order2,vnle_order3];
+
+        % %%%%% VNLE + DFE %%%%
+        if 0
+
+            eq_vnle_dfe     = EQ("Ne",vnle_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
+            eq_2 = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+
+            [result] = vnle(eq_vnle_dfe,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",doub_mode,"showAnalysis",1,"postFFE",[]);
+            vnle_dfe_package{iatt,occ} = result;
+
+        end
+
+        %%%%% VNLE + PF + MLSE %%%%
+        if 1
+            
+            try
+                % len_tr = length(Symbols)-1000;
+                eq_vnle_    = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+                % eq_vnle_ = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0,"order",vnle_order,"sps",2,"decide",0);
+                pf_         = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
+                mlse_       = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
+                eq_2 = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+    
+                [result] = vnle_postfilter_mlse(eq_vnle_,pf_,mlse_,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",doub_mode,'showAnalysis',0,"postFFE",[]);
+                vnle_pf_package{iatt,occ} = result;
+    
+                database.addProcessingResult(current_run_id,result.resultsMLSE, result.equalizerConfigMLSE);
+                database.addProcessingResult(current_run_id,result.resultsVNLE, result.equalizerConfigVNLE);
+            catch
+                warning(['VNLE+MLSE fail: run id: ', num2str(current_run_id)],' occ:', num2str(occ), ' iatten: ',num2str(iatt))
+            end
+
+        end
+
+        %%%%% Duobinary Targeting %%%%
+        if 1
+
+            try
+                mlse_db = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
+                eq_db = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+                eq_2 = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+
+                [result] = duobinary_target(eq_db, mlse_db, M, Scpe_sig, Symbols, Tx_bits, "precode_mode", doub_mode,'showAnalysis',0,"postFFE",[]);
+                dbtgt_package{iatt,occ} = result;
+
+                database.addProcessingResult(current_run_id,result.resultsDBtgt, result.equalizerConfigDBtgt);
+
+            catch
+                warning(['VNLE DB+MLSE fail: run id: ', num2str(current_run_id)],' occ:', num2str(occ), ' iatten: ',num2str(iatt))
+            end
+
+        end
+
+        %%%%%% %db signaling => db encoded %%%%%
+        if 0
+            mlse_db_enc = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
+            eq_db_enc = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+            [result] = duobinary_signaling(eq_db_enc, mlse_db_enc,M, Scpe_sig ,Symbols, Tx_bits);
+            dbenc_package{iatt,occ} = result;
+        end
+
+
+        % autoArrangeFigures;
+        disp('- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ')
+        fprintf('\n')
+
+
+    end
+
+
+
+    if ~isempty(curFolder)
+        cd(curFolder);
+    end
+
+end
+
+output.dataTable = dataTable;
+output.vnle_dfe_package = vnle_dfe_package;
+output.vnle_pf_package = vnle_pf_package;
+output.dbtgt_package = dbtgt_package;

projects/HighSpeedExperiment_2024/auswertung MPI/dsp_mpi_database.m

@@ -0,0 +1,61 @@
+
+% 1) Find RUN ID's
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+filterParams = database.tables;
+filterParams.Configurations = struct( ...
+    'bitrate',          [], ... %[224,336,360,390,420,448]
+    'db_mode',          [], ...
+    'fiber_length',     [], ...
+    'interference_attenuation',[], ...
+    'is_mpi',           0, ...
+    'pam_level',        [], ...
+    'rop_attenuation',  0 ...
+    );
+
+selectedFields = {'Runs.run_id',...
+    'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength',...
+    'Configurations.precomp_amp','Measurements.power_rop','Measurements.power_pd_in','Configurations.v_bias','Configurations.is_mpi',...
+    'Configurations.interference_attenuation','Configurations.rop_attenuation'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+
+% only the rows without BER so far
+% dataTable = dataTable(dataTable.BER == 0,:);
+dataTable = dataTable((dataTable.fiber_length ~= 1),:);
+
+% Ensure a parallel pool is running
+pool = gcp('nocreate');
+if isempty(pool)
+    pool = parpool;
+    % stop all forgotten or unfetched jobs from queue
+elseif ~isempty(pool.FevalQueue.QueuedFutures) || ~isempty(pool.FevalQueue.RunningFutures)
+    oldq = length(pool.FevalQueue.QueuedFutures) + length(pool.FevalQueue.RunningFutures);
+    pool.FevalQueue.cancelAll
+    fprintf('Canceled %d unfetched jobs from old queue.', oldq);
+end
+
+% Number of tasks to submit (one per run_id)
+nTasks = height(dataTable);
+futures = parallel.FevalFuture.empty();
+
+% Submit each DSP run as a parallel task using parfeval
+for i = 1:nTasks
+    % Extract the run_id (other parameters could be passed if needed)
+    runID = dataTable.run_id(i);
+    % Submit the function call to dsp_run_id (assuming it returns no output, hence 0 outputs)
+    futures(i) = parfeval(pool, @dsp_run_id, 0, runID, "max_occurences", 15, "append_to_db", 1);
+end
+
+% Set up a waitbar to monitor progress
+h = waitbar(0, 'Processing DSP runs...');
+while ~all(strcmp({futures.State}, 'finished'))
+    finishedCount = sum(strcmp({futures.State}, 'finished'));
+    waitbar(finishedCount / nTasks, h);
+    pause(0.1);
+end
+delete(h);
+
+fprintf('All DSP runs processed.\n');

projects/HighSpeedExperiment_2024/auswertung MPI/dsp_run_id.m

@@ -0,0 +1,194 @@
+function  [output] = dsp_run_id(run_id,options)
+
+arguments
+    run_id
+    options.append_to_db    = 0;
+    options.max_occurences  = 4;
+    options.parameters      = struct();
+end
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+filterParams = database.tables;
+filterParams.Configurations = struct('run_id', run_id);
+
+selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
+    'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','Measurements.power_rop','Configurations.v_bias',...
+    'Configurations.interference_attenuation'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+[~, uniqueIdx] = unique(dataTable.run_id);  % Get unique run_id indices
+dataTable = dataTable(uniqueIdx,:);  % Extract unique configurations for each run_id
+
+fsym = dataTable.symbolrate;
+M = double(dataTable.pam_level);
+duob_mode = db_mode(dataTable.db_mode);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+len_tr  = 4096*2;
+
+vnle_order1 = 50;
+vnle_order2 = 5;
+vnle_order3 = 5;
+
+dfe_order = [0 0 0];
+
+pf_ncoeffs = 1;
+
+mu_ffe1 = 0.0001;
+mu_ffe2 = 0.0008;
+mu_ffe3 = 0.001;
+mu_dfe = 0.0004;
+mu_dc = 0.00;
+
+mu_ffe = [mu_ffe1 mu_ffe2 mu_ffe3];
+vnle_order=[vnle_order1,vnle_order2,vnle_order3];
+
+% Overwrite default parameters if given in options.parameters
+paramStruct = options.parameters;
+if ~isempty(paramStruct)
+    paramNames = fieldnames(paramStruct);
+    for i = 1:numel(paramNames)
+        thisName = paramNames{i};
+        thisValue = paramStruct.(thisName);
+        eval([thisName ' = thisValue;']);
+    end
+end
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+eq_    = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+pf_    = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
+mlse_  = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
+mlse_db_ = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
+eq_post = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+
+output = struct();
+vnle_pf_package = {};
+vnle_dfe_package = {};
+dbtgt_package = {};
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+Tx_bits     = load([basePath, char(dataTable.tx_bits_path)]);
+Tx_bits     = Tx_bits.Bits;
+Symbols_mapped = PAMmapper(M,0).map(Tx_bits);
+Symbols_mapped.fs = dataTable.symbolrate;
+
+Symbols  = load([basePath, char(dataTable.tx_symbols_path)]);
+Symbols  = Symbols.Symbols;
+
+Scpe_load     = load([basePath, char(dataTable.rx_sync_path)]);
+Scpe_cell     = Scpe_load.S;
+[~,~,found]=Scpe_cell{2}.tsynch("reference",Symbols,"fs_ref",dataTable.symbolrate,"debug_plots",0);
+
+if ~found
+    Raw_signal = load([basePath, char(dataTable.rx_raw_path(1))]);
+    Raw_signal = Raw_signal.Scpe_sig_raw;
+    [~,Scpe_cell,found] =Raw_signal.tsynch("reference",Symbols,"fs_ref",dataTable.symbolrate,"debug_plots",0);
+end
+
+if ~found
+    if length(Symbols_mapped.signal) == sum(Symbols_mapped.signal == Symbols.signal)
+        warning('Could not synchronize the received signal with the stored symbols!')
+    else
+        [~,Scpe_cell,found] =Raw_signal.tsynch("reference",Symbols_mapped,"fs_ref",dataTable.symbolrate,"debug_plots",0);
+    end
+    if ~found
+        warning('Could not synchronize the received signal with the stored symbols!')
+    end
+end
+
+proc_occ = min(options.max_occurences,length(Scpe_cell));
+for occ = 1:proc_occ
+
+    Scpe_sig = Scpe_cell{occ};
+
+    %%%%%% Sample to 2x fsym %%%%%%
+    Scpe_sig =  Scpe_sig.resample("fs_out",2*fsym);
+
+    %%%%%% Sync Rx signal with reference %%%%%%
+    [Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
+
+    Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
+
+    Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
+
+    % Scpe_sig.plot("displayname",'Scope Signal','fignum',11);
+    % Scpe_sig.spectrum("displayname",'Raw Signal','fignum',20);
+
+    if duob_mode ~= db_mode.db_encoded
+        
+        % %%%%% VNLE + DFE %%%%
+        if 0
+    
+            eq_vnle_dfe     = EQ("Ne",vnle_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
+            eq_post = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+    
+            [result] = vnle(eq_vnle_dfe,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",duob_mode,"showAnalysis",1,"postFFE",[]);
+            vnle_dfe_package{occ} = result;
+    
+        end
+    
+        %%%%% VNLE + PF + MLSE %%%%
+        if 1
+    
+            [result] = vnle_postfilter_mlse(eq_,pf_,mlse_,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[],"eth_style_symbol_mapping",0);
+            vnle_pf_package{occ} = result;
+    
+            if options.append_to_db
+                database.addProcessingResult(run_id,result.resultsMLSE, result.equalizerConfigMLSE);
+                database.addProcessingResult(run_id,result.resultsVNLE, result.equalizerConfigVNLE);
+            end
+        end
+    
+        %%%%% Duobinary Targeting %%%%
+        if 1
+            [result] = duobinary_target(eq_, mlse_db_, M, Scpe_sig, Symbols, Tx_bits, "precode_mode", duob_mode,'showAnalysis',0,"postFFE",[]);
+            dbtgt_package{occ} = result;
+    
+            if options.append_to_db
+                database.addProcessingResult(run_id, result.resultsDBtgt, result.equalizerConfigDBtgt);
+            end
+        end
+
+       fprintf("BER VNLE: %.2e | %.2e; BER MLSE: %.2e | %.2e; BER DB tgt: %.2e | %.2e \n",vnle_pf_package{occ}.resultsVNLE.BER,vnle_pf_package{occ}.resultsVNLE.BER_precoded  ,vnle_pf_package{occ}.resultsMLSE.BER,vnle_pf_package{occ}.resultsMLSE.BER_precoded,dbtgt_package{occ}.resultsDBtgt.BER,dbtgt_package{occ}.resultsDBtgt.BER_precoded)
+       % fprintf("BER VNLE: %.2e | %.2e; BER MLSE: %.2e | %.2e \n",vnle_pf_package{occ}.resultsVNLE.BER,vnle_pf_package{occ}.resultsVNLE.BER_precoded  ,vnle_pf_package{occ}.resultsMLSE.BER,vnle_pf_package{occ}.resultsMLSE.BER_precoded);
+
+
+    else
+
+        %%%%%% %db signaling => db encoded %%%%%
+        if 1
+            mlse_db_enc = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
+            eq_db_enc = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+            [result] = duobinary_signaling(eq_db_enc, mlse_db_enc,M, Scpe_sig ,Symbols, Tx_bits);
+            dbenc_package{occ} = result;
+
+            if options.append_to_db
+                database.addProcessingResult(run_id, result.resultsDBsignaling, result.equalizerConfigDBsignaling);
+            end
+        end
+
+        fprintf("BER DB: %.2e \n",dbenc_package{occ}.resultsDBsignaling.BER);
+
+
+    end
+
+
+    % autoArrangeFigures;
+    disp('- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ')
+    fprintf('\n')
+
+
+end
+
+
+output.dataTable = dataTable;
+output.vnle_dfe_package = vnle_dfe_package;
+output.vnle_pf_package = vnle_pf_package;
+output.dbtgt_package = dbtgt_package;
+
+end

projects/HighSpeedExperiment_2024/auswertung MPI/plot_from_database.m

@@ -0,0 +1,150 @@
+
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+filterParams = database.tables;
+filterParams.Configurations = struct( ...
+    'bitrate',          [], ... %[224,336,360,390,420,448]
+    'db_mode',          int32(db_mode.no_db), ...
+    'fiber_length',     1, ...
+    'interference_attenuation', [], ...
+    'interference_path_length', [], ...
+    'is_mpi',           1, ...
+    'pam_level',        4, ...
+    'rop_attenuation',  0, ...
+    'wavelength', 1310 ...
+    );
+
+% filterParams.EqualizerParameters.diff_precode = int32(db_mode.no_db);
+ filterParams.EqualizerParameters.equalizer_structure = int32(equalizer_structure.vnle);
+% filterParams.EqualizerParameters.DCmu = 0.005;
+
+selectedFields = {'Configurations.run_id' 'Runs.rx_raw_path'	'Configurations.bitrate'	'Configurations.symbolrate'	'Configurations.pam_level'	'Configurations.db_mode'	'Configurations.rop_attenuation'	'Configurations.is_mpi'	'Configurations.interference_attenuation'	'EqualizerParameters.equalizer_structure'	'EqualizerParameters.diff_precode' 'EqualizerParameters.eq_id'	'Measurements.power_pd_in'	'Measurements.power_mpi_interference'	'Measurements.power_mpi_signal'	'Results.BER'	'Results.SNR'	'Results.GMI'	'Results.Alpha'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+
+fixedVars = {'run_id','eq_id','bitrate'};
+dataTableGrpd = groupIt(fixedVars,dataTable);
+
+
+% Create a new figure
+figure(3);
+hold on
+unique_rates = unique(dataTable.bitrate);
+cols = linspecer(8);
+for i = 1:numel(unique_rates)
+
+    % Plot BER vs. interference_attenuation
+    % plot(dataTableGrpd.power_mpi_signal(dataTableGrpd.bitrate==unique_rates(i),:)-dataTableGrpd.power_mpi_interference(dataTableGrpd.bitrate==unique_rates(i),:), dataTableGrpd.BER(dataTableGrpd.bitrate==unique_rates(i),:), '-', 'LineWidth', 0.5,'Color',cols(i,:));
+
+    if filterParams.Configurations.is_mpi
+        sir = dataTable.power_mpi_signal(dataTable.bitrate==unique_rates(i),:)-dataTable.power_mpi_interference(dataTable.bitrate==unique_rates(i),:);
+        ber = dataTable.BER(dataTable.bitrate==unique_rates(i),:);
+        sc=scatter(dataTable.power_mpi_signal(dataTable.bitrate==unique_rates(i),:)-dataTable.power_mpi_interference(dataTable.bitrate==unique_rates(i),:), dataTable.BER(dataTable.bitrate==unique_rates(i),:), 'LineWidth', 0.5,'Marker','.','MarkerEdgeColor',cols(i+1,:));
+        pair_one = {'Run ID', dataTable.run_id(dataTable.bitrate==unique_rates(i),:)};
+        pair_two = {'Rate', dataTable.bitrate(dataTable.bitrate==unique_rates(i),:)};
+        addDatatips(sc, pair_one, pair_two);
+    else
+        sc=scatter(62*ones(size( dataTableGrpd.BER(dataTableGrpd.bitrate==unique_rates(i),:))), dataTableGrpd.BER(dataTableGrpd.bitrate==unique_rates(i),:), 'LineWidth', 0.5,'Marker','o','MarkerEdgeColor',cols(i,:),'MarkerFaceColor',cols(i,:));
+        pair_one = {'Run ID', dataTableGrpd.run_id(dataTableGrpd.bitrate==unique_rates(i),:)};
+        pair_two = {'Rate', dataTableGrpd.bitrate(dataTableGrpd.bitrate==unique_rates(i),:)};
+        addDatatips(sc, pair_one, pair_two);
+    end
+
+
+
+end
+
+% Label the axes and add a title
+xlabel('SIR in dB');
+ylabel('BER');
+title('BER vs. Signal to Interference Ratio');
+yline(3.8e-3,'LineWidth',1,'LineStyle','--','HandleVisibility','off');
+% Enable grid for better readability
+grid on;
+
+beautifyBERplot;
+ylim([1e-4 0.5]);
+
+
+
+function resultTable = groupIt(fixedVars,dataTable)
+
+    % Group by run_id and eq_id (adjust grouping keys as needed)
+    
+    [G, groupKeys] = findgroups(dataTable(:, fixedVars));
+    
+    % Preallocate a cell array for aggregated data.
+    varNames = dataTable.Properties.VariableNames;
+    nVars = numel(varNames);
+    aggData = cell(height(groupKeys), nVars);
+    groupCount = zeros(height(groupKeys), 1);  % To store the size of each group
+    
+    % Loop over each group.
+    for i = 1:height(groupKeys)
+        idx = (G == i); % Logical index for group i
+        groupCount(i) = sum(idx);  % Count number of rows in this group
+        % For each variable in the table:
+        for j = 1:nVars
+            colData = dataTable.(varNames{j});
+            if isnumeric(colData)
+                % For numeric data, compute the mean.
+                aggData{i, j} = min(colData(idx));
+            else
+                % For non-numeric data, take the first entry.
+                if iscell(colData)
+                    aggData{i, j} = colData{find(idx, 1)};
+                else
+                    aggData{i, j} = colData(find(idx, 1));
+                end
+            end
+        end
+    end
+    
+    % Convert the aggregated cell array into a table.
+    resultTable = cell2table(aggData, 'VariableNames', varNames);
+    
+    % Append the group count as a new column.
+    resultTable.nRows = groupCount;
+
+end
+
+
+function addDatatips(sc, varargin)
+% addDatatips Adds custom data tip rows to a scatter plot.
+%
+%   addDatatips(sc, pair1, pair2, ...) adds one or more custom rows to the 
+%   data tip display of the scatter plot identified by sc.
+%
+%   Each pair should be provided as a 1x2 cell array: {label, value}.
+%   The value can be a scalar or a vector. If a vector is provided, its length
+%   must match the number of scatter plot points.
+%
+%   Example:
+%       sc = scatter(x, y, 'LineWidth', 1.5, 'Marker', 'o');
+%       pair_one = {'Attenuation', attenuationVector};
+%       addDatatips(sc, pair_one);
+
+    numPoints = numel(sc.XData);
+    
+    for k = 1:length(varargin)
+        pair = varargin{k};
+        
+        if ~iscell(pair) || numel(pair) ~= 2
+            error('Each pair must be a 1x2 cell array: {label, value}.');
+        end
+        
+        label = pair{1};
+        value = pair{2};
+        
+        % If value is a vector, ensure its length is either 1 or equal to the number of scatter points.
+        if isvector(value) && numel(value) ~= 1 && numel(value) ~= numPoints
+            error('The vector for "%s" must be a scalar or have %d elements matching the scatter data points.', label, numPoints);
+        end
+        
+        % Create a new data tip row using the provided label and vector.
+        newRow = dataTipTextRow(label, value);
+        sc.DataTipTemplate.DataTipRows(end+1) = newRow;
+    end
+end

projects/HighSpeedExperiment_2024/auswertung deliv 06 feb 2025/analyze_burg.m

@@ -0,0 +1,68 @@
+% basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+if 0
+
+    uloops              = struct;
+    uloops.precomp      = [0];
+    uloops.db_precode   = [0];
+    uloops.bitrate      = [330,390,450].*1e9; %[300,330,360,390,420,450,480]
+    uloops.laser_wavelength = [1310];
+    uloops.M            = [4];
+    uloops.link_length  = [2]; % 1,2,3,5,6,8,10
+    %uloops.alpha        = [0:0.1:1];
+
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    wh = submit_simulations(wh,"parallel",1,"simulation_mode",0);
+
+end
+
+col = cbrewer2('spectral',6);%
+col=linspecer(5);
+
+cnt = 1;
+for br = uloops.bitrate
+    a = wh_burg.getStoValue('ber',uloops.precomp, uloops.db_precode, br , uloops.laser_wavelength, uloops.M, uloops.link_length);
+    ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+    alpha = cellfun(@(x) x.vnle_pf_package{1,1}.pf.coefficients, a,'UniformOutput', false);
+    figure(23)
+    hold on
+    scatter(alpha{1}(2),ber_mlse,100,'MarkerEdgeColor',col(cnt,:),'Marker','x','LineWidth',2,'HandleVisibility','off');
+    cnt = cnt+1;
+end
+
+
+
+cnt = 1;
+alpha = [];
+
+for br = uloops.bitrate
+
+    a = wh_alphas.getStoValue('ber',uloops.precomp, uloops.db_precode, br , uloops.laser_wavelength, uloops.M, uloops.link_length, [0:0.1:1]);
+    ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+
+    x_ax =  [0:0.1:1];
+
+    figure(23)
+    hold on
+    % title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,uloops.M));
+    plot(x_ax,ber_mlse,'DisplayName',sprintf(' %d GBps PAM 4',br.*1e-9),'LineStyle','-','HandleVisibility','on','Color',col(cnt,:));
+
+    xticks(x_ax);
+    set(gca, 'YScale', 'log');
+    ylim([1e-5 0.4]);
+    xlim([min(x_ax), max(x_ax) ]);
+    yline([3.8e-3, 2e-2],'HandleVisibility','off');
+    legend
+    beautifyBERplot();
+    xlabel('Channel $\alpha$');
+    ylabel('BER');
+
+    cnt = cnt+1;
+
+end
+
+
+
+

projects/HighSpeedExperiment_2024/auswertung deliv 06 feb 2025/analyze_equalizer_taps.m

@@ -0,0 +1,57 @@
+% basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+if 0
+
+    uloops              = struct;
+    uloops.precomp      = [0];
+    uloops.db_precode   = [0];
+    uloops.bitrate      = [390].*1e9; %[300,330,360,390,420,450,480]
+    uloops.laser_wavelength = [1310];
+    uloops.M            = [4];
+    uloops.link_length  = [2]; % 1,2,3,5,6,8,10
+    uloops.vnle_order1  = [5,10:10:100];
+    uloops.vnle_order2  = [0];
+    uloops.vnle_order3  = [0];
+
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    wh = submit_simulations(wh,"parallel",1,"simulation_mode",0);
+
+end
+
+
+col = cbrewer2('spectral',6);%
+col=linspecer(5);
+cnt = 1;
+for n3 = uloops.vnle_order3
+
+    a = wh.getStoValue('ber',uloops.precomp, uloops.db_precode, uloops.bitrate , uloops.laser_wavelength, uloops.M, uloops.link_length,...
+        uloops.vnle_order1,...
+        uloops.vnle_order2,...
+        n3);
+
+    ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+    ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+    ber_db = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
+    log_bers = log10(ber_vnle + 1e-12);
+
+    figure(20)
+    hold on
+    title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,uloops.M));
+    % plot(uloops.vnle_order1,ber_vnle,'DisplayName',sprintf('Tx precomp. + VNLE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt,:));
+    plot(uloops.vnle_order1,ber_mlse,'DisplayName',sprintf('VNLE + Postfilter + ;MLSE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt,:));
+    plot(uloops.vnle_order1,ber_db,'DisplayName',sprintf('DB tgt. VNLE + MLSE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt+2,:));
+    xticks(uloops.vnle_order1([1:1:end]));
+    set(gca, 'YScale', 'log');
+    ylim([5e-5 0.4]);
+    xlim([min(uloops.vnle_order1), max(uloops.vnle_order1) ]);
+    yline([3.8e-3, 2e-2],'HandleVisibility','off');
+    legend
+    beautifyBERplot();
+    xlabel('Number of 1st order coeff.');
+    ylabel('BER');
+
+    cnt = cnt+1;
+end
+

projects/HighSpeedExperiment_2024/auswertung deliv 06 feb 2025/analyze_lambda.m

@@ -0,0 +1,50 @@
+if 0
+    uloops          = struct;
+    uloops.precomp      = [0];
+    uloops.db_precode   = [0,1];
+    uloops.bitrate      = [420].*1e9; %[300,330,360,390,420,450,480]
+    % uloops.laser_wavelength = [1293,1297.5,1302,1306.5,1310,1313.4,1318,1322.7,1327.4];
+    uloops.laser_wavelength = [1293, 1302,1310,1318,1327.4];
+    uloops.M            = [4,6,8];
+    uloops.link_length  = [5]; % 1,2,3,5,6,8,10
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    wh = submit_simulations(wh,"parallel",1,"simulation_mode",0);
+end
+
+col = cbrewer2('Set2',6);%
+col=linspecer(5);
+cnt = 1;
+
+m = 8;
+
+% a = wh.getStoValue('ber',1, 0, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+% ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+
+a = wh.getStoValue('ber',0, 0, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+
+a = wh.getStoValue('ber',0, 1, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+ber_db = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
+
+x_ax = uloops.laser_wavelength;
+
+figure(21)
+hold on
+% title(sprintf('%d km | %d GBd | PAM %d',uloops.link_length,uloops.bitrate/log2(m).*1e-9,m));
+% plot(x_ax,ber_vnle,'DisplayName',sprintf('Tx precomp. + VNLE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt+1,:));
+plot(x_ax,ber_mlse,'DisplayName',sprintf('VNLE + Postfilter + MLSE'),'LineStyle','-','HandleVisibility','on','Color',colorsets.DeepRed.RGB);
+% plot(x_ax,ber_db,'DisplayName',sprintf('DB tgt. VNLE + MLSE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt,:));
+xticks(x_ax([1:1:end]));
+set(gca, 'YScale', 'log');
+ylim([5e-5 0.4]);
+xlim([min(x_ax)-3, max(x_ax)+3 ]);
+yline([3.8e-3, 2e-2],'HandleVisibility','off');
+legend
+beautifyBERplot();
+xlabel('Number of 1st order coeff.');
+ylabel('BER');
+
+cnt = cnt+1;
+

projects/HighSpeedExperiment_2024/auswertung deliv 06 feb 2025/analyze_postfilter_taps.m

@@ -0,0 +1,70 @@
+% basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+if 0
+
+    uloops              = struct;
+    uloops.precomp      = [0];
+    uloops.db_precode   = [0];
+    uloops.bitrate      = [300,330,360,390,420,450,480].*1e9; %[300,330,360,390,420,450,480]
+    uloops.laser_wavelength = [1310];
+    uloops.M            = [4];
+    uloops.link_length  = [2]; % 1,2,3,5,6,8,10
+    uloops.vnle_order1  = [50];
+    uloops.vnle_order2  = [7];
+    uloops.vnle_order3  = [7];
+    uloops.pf_ncoeffs   = [1,2,3];
+
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    wh = submit_simulations(wh,"parallel",1,"simulation_mode",0);
+
+end
+
+col = cbrewer2('spectral',6);%
+col=linspecer(5);
+cnt = 1;
+alpha = [];
+for n = uloops.pf_ncoeffs
+
+    a = wh.getStoValue('ber',uloops.precomp, uloops.db_precode, uloops.bitrate , uloops.laser_wavelength, uloops.M, uloops.link_length,...
+        uloops.vnle_order1,...
+        uloops.vnle_order2,...
+        uloops.vnle_order3,...
+        n);
+
+    ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+    ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+
+    % PF = cellfun(@(x) x.vnle_pf_package{1,1}.pf.coefficients, a,'UniformOutput',false);
+    % 
+    % showTransferFunction(PF{3}.coefficients,"fignum",12,"color",clr.Set1.red,"DisplayName",['360 GBd']);
+    % 
+    % showTransferFunction(PF{4}.coefficients,"fignum",12,"color",clr.Set1.blue,"DisplayName",['390 GBd']);
+    % 
+    % showTransferFunction(PF{5}.coefficients,"fignum",12,'color',clr.Set1.green,"DisplayName",['420 GBd']);
+    % ber_db = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
+    
+    x_ax = uloops.bitrate.*1e-9;
+
+    figure(23)
+    hold on
+    title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,uloops.M));
+    if n==1
+        plot(x_ax,ber_vnle,'DisplayName',sprintf('Tx precomp. + VNLE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt+4,:));
+    end
+    plot(x_ax,ber_mlse,'DisplayName',sprintf('VNLE + Postfilter + ;MLSE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt,:));
+    % plot(x_ax,ber_db,'DisplayName',sprintf('DB tgt. VNLE + MLSE'),'LineStyle','-','HandleVisibility','on','Color',col(cnt+2,:));
+    xticks(x_ax([1:1:end]));
+    set(gca, 'YScale', 'log');
+    ylim([1e-5 0.4]);
+    xlim([min(x_ax(2:end)), max(x_ax) ]);
+    yline([3.8e-3, 2e-2],'HandleVisibility','off');
+    legend
+    beautifyBERplot();
+    xlabel('Gross Bitrate in Gbps');
+    ylabel('BER');
+
+    cnt = cnt+1;
+end
+

projects/HighSpeedExperiment_2024/db_auswertung/rate_vs_ber.m

@@ -0,0 +1,186 @@
+
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+filterParams = database.tables;
+filterParams.Configurations = struct( ...
+    'bitrate',          [], ... %[224,336,360,390,420,448]
+    'db_mode',          int32(db_mode.db_encoded), ...
+    'fiber_length',     10, ...
+    'interference_attenuation', [], ...
+    'interference_path_length', [], ...
+    'is_mpi',           0, ...
+    'pam_level',        4, ...
+    'rop_attenuation',  0, ...
+    'wavelength', 1310 ...
+    );
+
+% filterParams.EqualizerParameters.diff_precode = int32(db_mode.db_encoded);
+% filterParams.EqualizerParameters.equalizer_structure = int32(equalizer_structure.vnle);
+filterParams.EqualizerParameters.DCmu = 0.00;
+
+selectedFields = {'Configurations.run_id' 'Runs.rx_raw_path'	'Configurations.bitrate'	'Configurations.symbolrate'	'Configurations.pam_level'...
+    'Configurations.db_mode'	'Configurations.rop_attenuation'	'Configurations.is_mpi'	'Configurations.interference_attenuation'	...
+    'EqualizerParameters.equalizer_structure'	'EqualizerParameters.diff_precode' 'EqualizerParameters.eq_id'	'Measurements.power_pd_in' ...
+    'Measurements.power_mpi_interference'	'Measurements.power_mpi_signal'	'Results.BER' 'Results.BER_precoded'	'Results.SNR'	'Results.GMI'	'Results.Alpha' 'Results.date_of_processing'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+
+fixedVars = {'eq_id','bitrate'};
+dataTableGrpd = groupIt(fixedVars,dataTable);
+
+
+plotRealizations = 0;
+
+% Create a new figure
+figure();
+hold on
+unique_eq = unique(dataTable.eq_id);
+cols = linspecer(8);
+for i = 1:numel(unique_eq)
+
+    idx = find(dataTableGrpd.eq_id == unique_eq(i), 1, 'first');
+    equalizer_ = equalizer_structure(dataTableGrpd.equalizer_structure(idx));
+
+
+    loop_filt = dataTableGrpd.eq_id==unique_eq(i);
+
+    % Plot LINE: BER vs. interference_attenuation
+    switch equalizer_
+        case equalizer_structure.vnle
+            bers = dataTableGrpd.BER(loop_filt,:);
+        case equalizer_structure.vnle_pf_mlse
+            bers = dataTableGrpd.BER(loop_filt,:);
+        case equalizer_structure.vnle_db_mlse
+            bers = dataTableGrpd.BER_precoded(loop_filt,:);
+        case equalizer_structure.db_encoded
+            bers = dataTableGrpd.BER(loop_filt,:);
+    end
+
+    
+    name = sprintf('%s',equalizer_);
+
+    p = plot(dataTableGrpd.bitrate(loop_filt,:).*1e-9, bers, '-', 'LineWidth', 0.5,'Color',cols(i,:),'DisplayName',name);
+    pair_one = {'Run ID', dataTableGrpd.run_id(loop_filt,:)};
+    pair_two = {'Rate', dataTableGrpd.bitrate(loop_filt,:)};
+    addDatatips(p, pair_one, pair_two);
+    xticks(unique(dataTableGrpd.bitrate(loop_filt,:).*1e-9));
+
+    % Plot SCATTERS: BER vs. interference_attenuation
+
+    loop_filt = dataTable.eq_id==unique_eq(i);
+    if plotRealizations
+        switch equalizer_
+            case equalizer_structure.vnle
+                bers = dataTable.BER(loop_filt,:);
+            case equalizer_structure.vnle_pf_mlse
+                bers = dataTable.BER(loop_filt,:);
+            case equalizer_structure.vnle_db_mlse
+                bers = dataTable.BER_precoded(loop_filt,:);
+            case equalizer_structure.db_encoded
+                bers = dataTable.BER(loop_filt,:);
+        end
+        
+        sc = scatter(dataTable.bitrate(loop_filt,:).*1e-9, bers, 'LineWidth', 0.5,'Marker','*','MarkerEdgeColor',cols(i,:),'HandleVisibility','off');
+        pair_one = {'Run ID', dataTable.run_id(loop_filt,:)};
+        pair_two = {'Rate', dataTable.bitrate(loop_filt,:)};
+        addDatatips(sc, pair_one, pair_two);
+        xticks(unique(dataTable.bitrate(loop_filt,:).*1e-9));
+    end
+
+end
+
+
+% Label the axes and add a title
+xlabel('Bitrate in Gbps');
+ylabel('BER');
+title('Line Rate vs. BER');
+yline(3.8e-3,'LineWidth',1,'LineStyle','--','HandleVisibility','off');
+% Enable grid for better readability
+grid on;
+
+beautifyBERplot;
+ylim([1e-4 0.5]);
+
+
+
+function resultTable = groupIt(fixedVars,dataTable)
+
+    % Group by run_id and eq_id (adjust grouping keys as needed)
+    
+    [G, groupKeys] = findgroups(dataTable(:, fixedVars));
+    
+    % Preallocate a cell array for aggregated data.
+    varNames = dataTable.Properties.VariableNames;
+    nVars = numel(varNames);
+    aggData = cell(height(groupKeys), nVars);
+    groupCount = zeros(height(groupKeys), 1);  % To store the size of each group
+    
+    % Loop over each group.
+    for i = 1:height(groupKeys)
+        idx = (G == i); % Logical index for group i
+        groupCount(i) = sum(idx);  % Count number of rows in this group
+        % For each variable in the table:
+        for j = 1:nVars
+            colData = dataTable.(varNames{j});
+            if isnumeric(colData)
+                % For numeric data, compute the mean.
+                aggData{i, j} = min(colData(idx));
+            else
+                % For non-numeric data, take the first entry.
+                if iscell(colData)
+                    aggData{i, j} = colData{find(idx, 1)};
+                else
+                    aggData{i, j} = colData(find(idx, 1));
+                end
+            end
+        end
+    end
+    
+    % Convert the aggregated cell array into a table.
+    resultTable = cell2table(aggData, 'VariableNames', varNames);
+    
+    % Append the group count as a new column.
+    resultTable.nRows = groupCount;
+
+end
+
+
+function addDatatips(sc, varargin)
+% addDatatips Adds custom data tip rows to a scatter plot.
+%
+%   addDatatips(sc, pair1, pair2, ...) adds one or more custom rows to the 
+%   data tip display of the scatter plot identified by sc.
+%
+%   Each pair should be provided as a 1x2 cell array: {label, value}.
+%   The value can be a scalar or a vector. If a vector is provided, its length
+%   must match the number of scatter plot points.
+%
+%   Example:
+%       sc = scatter(x, y, 'LineWidth', 1.5, 'Marker', 'o');
+%       pair_one = {'Attenuation', attenuationVector};
+%       addDatatips(sc, pair_one);
+
+    numPoints = numel(sc.XData);
+    
+    for k = 1:length(varargin)
+        pair = varargin{k};
+        
+        if ~iscell(pair) || numel(pair) ~= 2
+            error('Each pair must be a 1x2 cell array: {label, value}.');
+        end
+        
+        label = pair{1};
+        value = pair{2};
+        
+        % If value is a vector, ensure its length is either 1 or equal to the number of scatter points.
+        if isvector(value) && numel(value) ~= 1 && numel(value) ~= numPoints
+            error('The vector for "%s" must be a scalar or have %d elements matching the scatter data points.', label, numPoints);
+        end
+        
+        % Create a new data tip row using the provided label and vector.
+        newRow = dataTipTextRow(label, value);
+        sc.DataTipTemplate.DataTipRows(end+1) = newRow;
+    end
+end

projects/HighSpeedExperiment_2024/db_auswertung/realization_vs_ber.m

@@ -0,0 +1,164 @@
+
+
+basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
+database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
+
+filterParams = database.tables;
+filterParams.Configurations = struct( ...
+    'bitrate',          450e9, ... %[224,336,360,390,420,448]
+    'db_mode',          int32(db_mode.no_db), ...
+    'fiber_length',     10, ...
+    'interference_attenuation', [], ...
+    'interference_path_length', [], ...
+    'is_mpi',           0, ...
+    'pam_level',        4, ...
+    'rop_attenuation',  0, ...
+    'wavelength', 1310 ...
+    );
+
+% filterParams.EqualizerParameters.diff_precode = int32(db_mode.db_encoded);
+% filterParams.EqualizerParameters.equalizer_structure = int32(equalizer_structure.vnle);
+filterParams.EqualizerParameters.DCmu = 0.00;
+
+selectedFields = {'Configurations.run_id' 'Runs.rx_raw_path'	'Configurations.bitrate'	'Configurations.symbolrate'	'Configurations.pam_level'...
+    'Configurations.db_mode'	'Configurations.rop_attenuation'	'Configurations.is_mpi'	'Configurations.interference_attenuation'	...
+    'EqualizerParameters.equalizer_structure'	'EqualizerParameters.diff_precode' 'EqualizerParameters.eq_id'	'Measurements.power_pd_in' ...
+    'Measurements.power_mpi_interference'	'Measurements.power_mpi_signal'	'Results.BER' 'Results.BER_precoded'	'Results.SNR'	'Results.GMI'	'Results.Alpha' 'Results.date_of_processing'};
+
+[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
+
+fixedVars = {'eq_id','bitrate'};
+dataTableGrpd = groupIt(fixedVars,dataTable);
+
+
+plotRealizations = 1;
+
+% Create a new figure
+figure();
+hold on
+unique_eq = unique(dataTable.eq_id);
+cols = linspecer(8);
+
+for i = 1:numel(unique_eq)
+
+    idx = find(dataTableGrpd.eq_id == unique_eq(i), 1, 'first');
+    equalizer_ = equalizer_structure(dataTableGrpd.equalizer_structure(idx));
+
+    % Plot SCATTERS: timestamp vs. interference_attenuation
+
+    loop_filt = dataTable.eq_id==unique_eq(i);
+    if plotRealizations
+        switch equalizer_
+            case equalizer_structure.vnle
+                bers = dataTable.BER(loop_filt,:);
+            case equalizer_structure.vnle_pf_mlse
+                bers = dataTable.BER(loop_filt,:);
+            case equalizer_structure.vnle_db_mlse
+                bers = dataTable.BER_precoded(loop_filt,:);
+            case equalizer_structure.db_encoded
+                bers = dataTable.BER(loop_filt,:);
+        end
+        date_of_proc = datetime(dataTable.date_of_processing(loop_filt,:));
+        
+        sc = scatter(date_of_proc, bers, 'LineWidth', 0.5,'Marker','*','MarkerEdgeColor',cols(i,:),'HandleVisibility','off');
+        pair_one = {'Run ID', dataTable.run_id(loop_filt,:)};
+        pair_two = {'Rate', dataTable.bitrate(loop_filt,:)};
+        addDatatips(sc, pair_one, pair_two);
+        xticks(date_of_proc);
+    end
+
+end
+
+
+% Label the axes and add a title
+xlabel('Time of Processing');
+ylabel('BER');
+title('Line Rate vs. BER');
+yline(3.8e-3,'LineWidth',1,'LineStyle','--','HandleVisibility','off');
+% Enable grid for better readability
+grid on;
+
+beautifyBERplot;
+ylim([1e-4 0.5]);
+
+
+
+function resultTable = groupIt(fixedVars,dataTable)
+
+    % Group by run_id and eq_id (adjust grouping keys as needed)
+    
+    [G, groupKeys] = findgroups(dataTable(:, fixedVars));
+    
+    % Preallocate a cell array for aggregated data.
+    varNames = dataTable.Properties.VariableNames;
+    nVars = numel(varNames);
+    aggData = cell(height(groupKeys), nVars);
+    groupCount = zeros(height(groupKeys), 1);  % To store the size of each group
+    
+    % Loop over each group.
+    for i = 1:height(groupKeys)
+        idx = (G == i); % Logical index for group i
+        groupCount(i) = sum(idx);  % Count number of rows in this group
+        % For each variable in the table:
+        for j = 1:nVars
+            colData = dataTable.(varNames{j});
+            if isnumeric(colData)
+                % For numeric data, compute the mean.
+                aggData{i, j} = min(colData(idx));
+            else
+                % For non-numeric data, take the first entry.
+                if iscell(colData)
+                    aggData{i, j} = colData{find(idx, 1)};
+                else
+                    aggData{i, j} = colData(find(idx, 1));
+                end
+            end
+        end
+    end
+    
+    % Convert the aggregated cell array into a table.
+    resultTable = cell2table(aggData, 'VariableNames', varNames);
+    
+    % Append the group count as a new column.
+    resultTable.nRows = groupCount;
+
+end
+
+
+function addDatatips(sc, varargin)
+% addDatatips Adds custom data tip rows to a scatter plot.
+%
+%   addDatatips(sc, pair1, pair2, ...) adds one or more custom rows to the 
+%   data tip display of the scatter plot identified by sc.
+%
+%   Each pair should be provided as a 1x2 cell array: {label, value}.
+%   The value can be a scalar or a vector. If a vector is provided, its length
+%   must match the number of scatter plot points.
+%
+%   Example:
+%       sc = scatter(x, y, 'LineWidth', 1.5, 'Marker', 'o');
+%       pair_one = {'Attenuation', attenuationVector};
+%       addDatatips(sc, pair_one);
+
+    numPoints = numel(sc.XData);
+    
+    for k = 1:length(varargin)
+        pair = varargin{k};
+        
+        if ~iscell(pair) || numel(pair) ~= 2
+            error('Each pair must be a 1x2 cell array: {label, value}.');
+        end
+        
+        label = pair{1};
+        value = pair{2};
+        
+        % If value is a vector, ensure its length is either 1 or equal to the number of scatter points.
+        if isvector(value) && numel(value) ~= 1 && numel(value) ~= numPoints
+            error('The vector for "%s" must be a scalar or have %d elements matching the scatter data points.', label, numPoints);
+        end
+        
+        % Create a new data tip row using the provided label and vector.
+        newRow = dataTipTextRow(label, value);
+        sc.DataTipTemplate.DataTipRows(end+1) = newRow;
+    end
+end

projects/IMDD_base_system/imdd_it.m

@@ -5,141 +5,307 @@ if 1
     uloops          = struct;
     uloops.precomp      = [1];
     uloops.db_precode   = [0];
-    uloops.bitrate      = [300,330,360,390,420,450,480].*1e9; %[300,330,360,390,420,450,480]
-    % uloops.bitrate      = 390e9;
+    uloops.bitrate      = [224].*1e9; %[300,330,360,390,420,450,480] [224,336,360,390,420,448] for MPI
     % uloops.laser_wavelength = [1293,1297.5,1302,1306.5,1310,1313.4,1318,1322.7,1327.4];
     uloops.laser_wavelength = [1310];
-    uloops.M            = [6];
-    uloops.link_length  = [2]; % 1,2,3,5,6,8,10
+    uloops.M            = [4];
+    uloops.link_length  = [1]; % 1,2,3,5,6,8,10
+    uloops.interference_attenuation = [0,3,6,9,12,15,18,21,24,27,30,45];
     wh = DataStorage(uloops);
     wh.addStorage("ber");
 
-    wh = submit_simulations(wh,"parallel",0,"simulation_mode",0);
+    % wh = submit_simulations(wh,"parallel",0,"simulation_mode",0);
+    wh = submit_handle(@imdd_model,wh,"parallel",1);
+
 end
 
-wh_ana = wh;
+wh_ana = wh_master;
 
-ber_mlse = {};
-ber_vnle = {};
-inf_rate_vnle ={};
+cols = cbrewer2('Paired',8);
 
-ber_dbtgt ={};
+figure()
 
-ber_dbenc ={};
-alpha = {};
-ber_dfe = {};
-ngmi     = [];
+for precomp = [0,1]
+    wavelength=uloops.laser_wavelength;
+    for m = [6]
 
-wavelength=uloops.laser_wavelength;
-for m = [4,6,8]
-    %1302
-    %VNLE
-    precomp = 1;
-    precode = 0;
-    a = wh_ana.getStoValue('ber',precomp, precode, uloops.bitrate , wavelength, m, uloops.link_length);
-    ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
-    
-    %MLSE
-    % precomp = 0;
-    % precode = 1;
-    a = wh_ana.getStoValue('ber',precomp, precode, uloops.bitrate , wavelength, m, uloops.link_length);
-    ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
-    
-    %DB
-    % precomp = 0;
-    % precode = 1;
-    a = wh_ana.getStoValue('ber',precomp, precode, uloops.bitrate , wavelength, m, uloops.link_length);
-    ber_dbtgt = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
-    
-    figure(m+20)
-    hold on
-    title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,m));
-    
-    plot(uloops.bitrate,ber_vnle,'DisplayName',sprintf('VNLE'),'Color',cols(3,:),'LineStyle','-','HandleVisibility','on');
-    
-    plot(uloops.bitrate,ber_dbtgt,'DisplayName',sprintf('DB tgt. + MLSE',uloops.link_length,uloops.M),'Color',cols(1,:),'LineStyle','-','HandleVisibility','on');
-    
-    plot(uloops.bitrate,ber_mlse,'DisplayName',sprintf('VNLE + 1 tap post-filter + MLSE',uloops.link_length,uloops.M),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
-    
-    set(gca, 'YScale', 'log');
-    ylim([5e-5 0.3]);
-    % xlim([min(uloops.bitrate.*1e-9), max(uloops.bitrate.*1e-9) ]);
-    yline([3.8e-3, 2e-2],'HandleVisibility','off');
-    legend
-    beautifyBERplot()
-    xlabel('Bit Rate in Gbps');
-    ylabel('BER');
-end
+        baudrate = wh_ana.parameter.bitrate.values;
 
 
-cols = linspecer(7);%cbrewer2('Set2',10);
+        %VNLE
+        precode = 1;
+        a = wh_ana.getStoValue('ber',precomp, precode, baudrate , wavelength, m, uloops.link_length);
+        ber_vnle_pc = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+        %MLSE
+        ber_mlse_pc = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+        %DB
+        ber_dbtgt_pc = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
 
+        precode = 0;
+        a = wh_ana.getStoValue('ber',precomp, precode, baudrate , wavelength, m, uloops.link_length);
+        ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+        %MLSE
+        ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+        %DB
+        ber_dbtgt = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
 
-for w = uloops.laser_wavelength
-
-    figure(w)
-    figcnt = 0;
-
-    for precode = uloops.db_precode
-    
-        for precomp = uloops.precomp
-
-           for m = uloops.M
-    
-            a = wh_ana.getStoValue('ber',precomp, precode, uloops.bitrate , w, m, uloops.link_length);
-            ber_dbtgt = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
-
-            ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
-
-            ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
-        
-            figcnt = figcnt+1;
-            subplot(4,3,figcnt);
-            hold on
-            title(sprintf('precomp = %d | precode = %d | %d km | %d nm | PAM %d',precomp,precode,uloops.link_length,w,m));
-            
-            plot(uloops.bitrate,ber_dbtgt,'DisplayName',sprintf('DB tgt. + MLSE',uloops.link_length,uloops.M),'Color',cols(1,:),'LineStyle','-','HandleVisibility','on');
-            
-            plot(uloops.bitrate,ber_vnle,'DisplayName',sprintf('VNLE'),'Color',cols(3,:),'LineStyle','-','HandleVisibility','on');
-            
-            plot(uloops.bitrate,ber_mlse,'DisplayName',sprintf('VNLE + 1 tap post-filter + MLSE',uloops.link_length,uloops.M),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
-            
-            % plot(uloops.bitrate,cellfun(@min, ber_dfe),'DisplayName',sprintf('VNLE + DFE',uloops.link_length,uloops.M),'Color',cols(2,:),'LineStyle','--');
-            
-            % plot(uloops.bitrate,cellfun(@min, ber_dbenc),'DisplayName',sprintf('DB Encoded',uloops.link_length,uloops.M),'Color',cols(5,:),'LineStyle','-');
-            
-            set(gca, 'YScale', 'log');
-            ylim([5e-5 0.5]);
-            % xlim([min(uloops.bitrate.*1e-9), max(uloops.bitrate.*1e-9) ]);
-            yline([3.8e-3, 2e-2],'HandleVisibility','off');
-            legend
-            beautifyBERplot()
-            xlabel('Bit Rate in Gbps');
-            ylabel('Channel Wavelength (nm)');
-        
-            end
+        if precomp
+            legndname1 = ['Pre-Emphasis'];
+        else
+            legndname1 = ['No Pre-Emphasis'];
         end
+
+
+        baudrate = floor( uloops.bitrate.*1e-9 ./log2(m) ) .* 2.5 .* 1e9;
+
+        subplot(1,3,1)
+        hold on
+        title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,m));
+        title(sprintf('PAM %d',m));
+        plot(baudrate.*1e-9,ber_vnle,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 0'],'Color',cols(1+precomp,:),'LineStyle','-','HandleVisibility','on');
+        plot(baudrate.*1e-9,ber_vnle_pc,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 1'],'Color',cols(1+precomp,:),'LineStyle','-.','HandleVisibility','on');
+        xticks(baudrate.*1e-9);
+        set(gca, 'YScale', 'log');
+        ylim([5e-5 0.4]);
+        xlim([min(baudrate(2).*1e-9), max(baudrate.*1e-9) ]);
+        yline([3.8e-3, 2e-2],'HandleVisibility','off');
+        legend
+        beautifyBERplot()
+        xlabel('Bit Rate in Gbps');
+        ylabel('BER');
+
+
+
+        subplot(1,3,2)
+        hold on
+        % title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,m));
+        title(sprintf('PAM %d',m));
+        plot(baudrate.*1e-9,ber_dbtgt,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 0'],'Color',cols(5+precomp,:),'LineStyle','-','HandleVisibility','on');
+        plot(baudrate.*1e-9,ber_dbtgt_pc,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 1'],'Color',cols(5+precomp,:),'LineStyle','-.','HandleVisibility','on');
+        xticks(baudrate.*1e-9);
+        set(gca, 'YScale', 'log');
+        ylim([5e-5 0.4]);
+        xlim([min(baudrate(2).*1e-9), max(baudrate.*1e-9) ]);
+        yline([3.8e-3, 2e-2],'HandleVisibility','off');
+        legend
+        beautifyBERplot()
+        xlabel('Bit Rate in Gbps');
+        ylabel('BER');
+
+
+        subplot(1,3,3)
+        hold on
+        % title(sprintf('%d km | %d nm | PAM %d',uloops.link_length,wavelength,m));
+        title(sprintf('PAM %d',m));
+        plot(baudrate.*1e-9,ber_mlse,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 0'],'Color',cols(3+precomp,:),'LineStyle','-','HandleVisibility','on');
+        plot(baudrate.*1e-9,ber_mlse_pc,'DisplayName',['Pre-Emphasis: ', num2str(precomp), '| Diff.-Code: 1'],'Color',cols(3+precomp,:),'LineStyle','-.','HandleVisibility','on');
+        xticks(baudrate.*1e-9);
+        set(gca, 'YScale', 'log');
+        ylim([5e-5 0.4]);
+        xlim([min(baudrate(2).*1e-9), max(baudrate.*1e-9) ]);
+        yline([3.8e-3, 2e-2],'HandleVisibility','off');
+        legend
+        beautifyBERplot()
+        xlabel('Bit Rate in Gbps');
+        ylabel('BER');
     end
 end
+%
+%
+% cols = linspecer(7);%cbrewer2('Set2',10);
+%
+%
+% for w = uloops.laser_wavelength
+%
+%     figure(w)
+%     figcnt = 0;
+%
+%     for precode = uloops.db_precode
+%
+%         for precomp = uloops.precomp
+%
+%             for m = uloops.M
+%
+%                 a = wh_ana.getStoValue('ber',precomp, precode, uloops.bitrate , w, m, uloops.link_length);
+%                 ber_dbtgt = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
+%
+%                 ber_vnle = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+%
+%                 ber_mlse = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+%
+%                 figcnt = figcnt+1;
+%                 subplot(4,3,figcnt);
+%                 hold on
+%                 title(sprintf('precomp = %d | precode = %d | %d km | %d nm | PAM %d',precomp,precode,uloops.link_length,w,m));
+%
+%                 plot(uloops.bitrate,ber_dbtgt,'DisplayName',sprintf('DB tgt. + MLSE',uloops.link_length,uloops.M),'Color',cols(1,:),'LineStyle','-','HandleVisibility','on');
+%
+%                 plot(uloops.bitrate,ber_vnle,'DisplayName',sprintf('VNLE'),'Color',cols(3,:),'LineStyle','-','HandleVisibility','on');
+%
+%                 plot(uloops.bitrate,ber_mlse,'DisplayName',sprintf('VNLE + 1 tap post-filter + MLSE',uloops.link_length,uloops.M),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+%
+%                 % plot(uloops.bitrate,cellfun(@min, ber_dfe),'DisplayName',sprintf('VNLE + DFE',uloops.link_length,uloops.M),'Color',cols(2,:),'LineStyle','--');
+%
+%                 % plot(uloops.bitrate,cellfun(@min, ber_dbenc),'DisplayName',sprintf('DB Encoded',uloops.link_length,uloops.M),'Color',cols(5,:),'LineStyle','-');
+%
+%                 set(gca, 'YScale', 'log');
+%                 ylim([5e-5 0.5]);
+%                 % xlim([min(uloops.bitrate.*1e-9), max(uloops.bitrate.*1e-9) ]);
+%                 yline([3.8e-3, 2e-2],'HandleVisibility','off');
+%                 legend
+%                 beautifyBERplot()
+%                 xlabel('Bit Rate in Gbps');
+%                 ylabel('Channel Wavelength (nm)');
+%
+%             end
+%         end
+%     end
+% end
 
-tp = TransmissionPerformance;
-netRatesVNLE = tp.calculateNetRate(uloops.bitrate, 'NGMI', cellfun(@min, inf_rate_vnle)./log2(uloops.M), 'BER', cellfun(@min, ber_vnle));
 
-pam8= [2.9515    2.9284    2.9203    2.9311    2.8473    2.7740    2.6253];
-pam6 = [2.5280    2.5452    2.5579    2.5549    2.5272    2.4243    2.2617];
-pam4 = [ 1.9982    1.9972    1.9690    1.7909    1.2493    0.8014    0.6385];
 
-figure(6)
-hold on
-title(sprintf('Performance at 1310 for all lengths'));
-% plot(uloops.bitrate.*1e-9,cellfun(@min, inf_rate_vnle),'DisplayName',sprintf('NGMI VNLE; %d km',uloops.link_length),'Color',cols(3,:),'LineStyle',':');
-plot(uloops.bitrate.*1e-9,pam4/2,'DisplayName',sprintf('GMI VNLE; PAM 4'),'Color',cols(1,:),'LineStyle',':');
-plot(uloops.bitrate.*1e-9,pam6/log2(6),'DisplayName',sprintf('GMI VNLE; PAM 6'),'Color',cols(2,:),'LineStyle',':');
-plot(uloops.bitrate.*1e-9,pam8/3,'DisplayName',sprintf('GMI VNLE; PAM 8'),'Color',cols(3,:),'LineStyle',':');
-xlabel('Gross Bitrate in Gbps');
-ylabel('NGMI')
-beautifyBERplot()
-ylim([0,1]);
+m = 6;
+ir = [2,2.5,3];
+cols = linspecer(6);
+baudrate_gather = [];
+for i = 1:3
+    m = uloops.M(i);
+
+    %%% GET VNLE VALS 
+    precode = 0;
+    precomp = 1;
+    a = wh_master.getStoValue('ber',precomp, precode, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+    ber_vnle(i,:) = cellfun(@(x) x.vnle_pf_package{1,1}.ber_vnle, a);
+
+    %%% GET DB VALS 
+    precode = 1;
+    precomp = 0;
+    a = wh_master.getStoValue('ber',precomp, precode, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+    ber_db(i,:) = cellfun(@(x) x.dbtgt_package{1,1}.ber, a);
+
+    %%% GET MLSE VALS 
+    precode = 0;
+    precomp = 0;
+    a = wh_master.getStoValue('ber',precomp, precode, uloops.bitrate , uloops.laser_wavelength, m, uloops.link_length);
+    ber_mlse(i,:) = cellfun(@(x) x.vnle_pf_package{1,1}.ber_mlse, a);
+
+    inf_rate_pam(i,:) = cellfun(@(x) x.vnle_pf_package{1,1}.air, a);
+    inf_rate_pam(i,:) = inf_rate_pam(i,:)./log2(m);
+
+    bitrate = floor( uloops.bitrate.*1e-9 ./log2(m) ) .* ir(i) .* 1e9;
+    baudrate = floor( uloops.bitrate.*1e-9 ./log2(m) )  .* 1e9;
+    baudrate_gather = union(baudrate_gather,baudrate);
+    baudrate_ticks = 100:20:240;
+    bitrate_ticks = 300:30:480;
+
+    tp = TransmissionPerformance;
+    netRatesVNLE = tp.calculateNetRate(bitrate, 'NGMI', inf_rate_pam(i,:), 'BER', ber_vnle(i,:));
+
+    %%% NGMI
+    figure(12)
+    hold on
+    title(sprintf('Performance at 1310 nm'));
+    plot(baudrate.*1e-9,inf_rate_pam(i,:),'DisplayName',sprintf('NGMI; PAM %d',m),'Color',cols(i,:),'LineStyle','-');
+    xlabel('Baud rate in GBd');
+    ylabel('NGMI')
+    beautifyBERplot()
+    xticks(baudrate_ticks);
+    xlim([min(baudrate_ticks) max(baudrate_ticks)]);
+
+
+    %%% AIR
+    figure(14)
+    hold on
+    title(sprintf('Performance at 1310 nm'));
+    plot(baudrate.*1e-9,inf_rate_pam(i,:).*bitrate.*1e-9,'DisplayName',sprintf('AIR; PAM %d',m),'Color',cols(i,:),'LineStyle','-');
+    xlabel('Baud rate in GBd');
+    ylabel('AIR');
+    beautifyBERplot()
+    xticks(baudrate_ticks);
+    xlim([min(baudrate_ticks) max(baudrate_ticks)]);
+
+    %%% RATES
+    figure(16)
+    hold on
+    title(sprintf('Performance at 1310 nm'));
+    if i == 1
+        hv = 'on';
+    else
+        hv = 'off';
+    end
+    plot(baudrate*1e-9,netRatesVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('SD+HD FEC',m),'Color',cols(i,:),'LineStyle','-','HandleVisibility',hv,'Marker','o');
+    plot(baudrate.*1e-9,netRatesVNLE.HD.NetRate.*1e-9,'DisplayName',sprintf('HD FEC',m),'Color',cols(i,:),'LineStyle',':','HandleVisibility',hv,'Marker','diamond');
+    plot(baudrate.*1e-9,netRatesVNLE.KP4_hamming.NetRate*1e-9,'DisplayName',sprintf('KP4+Hamming',m),'Color',cols(i,:),'LineStyle','-.','HandleVisibility',hv,'Marker','square');
+    xticks(baudrate_ticks);
+    xlim([min(baudrate_ticks) max(baudrate_ticks)]);
+    xlabel('Baud rate in GBd');
+    ylabel('Net Bitrate in Gbps')
+    beautifyBERplot()
+    ylim([250 410])
+
+    %%% CODE OVERHEAD IN %
+    figure(18)
+    hold on
+    title(sprintf('Performance at 1310 nm'));
+    plot(baudrate*1e-9,100.*(1-netRatesVNLE.SDHD.CodeRate)./netRatesVNLE.SDHD.CodeRate,'DisplayName',sprintf('SD+HD FEC',m),'Color',cols(i,:),'LineStyle','-','HandleVisibility',hv,'Marker','o');
+    plot(baudrate.*1e-9,100.*(1-netRatesVNLE.HD.CodeRate)./netRatesVNLE.HD.CodeRate,'DisplayName',sprintf('HD FEC',m),'Color',cols(i,:),'LineStyle',':','HandleVisibility',hv,'Marker','diamond');
+    plot(baudrate.*1e-9,100.*(1-netRatesVNLE.KP4_hamming.CodeRate)./netRatesVNLE.KP4_hamming.CodeRate,'DisplayName',sprintf('KP4+Hamming',m),'Color',cols(i,:),'LineStyle','-.','HandleVisibility',hv,'Marker','square');
+    xticks(baudrate_ticks);
+    xlim([min(baudrate_ticks) max(baudrate_ticks)]);
+    xlabel('Baud rate in GBd');
+    ylabel('FEC Overhead in %')
+    beautifyBERplot()
+
+    %%% CLASSIC BER
+    figure(22)
+    subplot(1,4,i)
+    hold on
+    plot(baudrate*1e-9,ber_vnle(i,:),'DisplayName',sprintf('Tx precomp + VNLE',m),'Color',cols(i,:),'LineStyle','-','HandleVisibility','on','Marker','o');
+    plot(baudrate*1e-9,ber_mlse(i,:),'DisplayName',sprintf('VNLE + PF + MLSE',m),'Color',cols(i,:),'LineStyle',':','HandleVisibility','on','Marker','square');
+    plot(baudrate*1e-9,ber_db(i,:),'DisplayName',sprintf('Diff. Code + DB tgt.',m),'Color',cols(i,:),'LineStyle','--','HandleVisibility','on','Marker','diamond');
+    yline(4.85e-3,'HandleVisibility','off');
+    yline(2e-2,'HandleVisibility','off');
+    xticks(baudrate*1e-9);
+    xlim([min(baudrate*1e-9) max(baudrate*1e-9)]);
+    ylim([1e-4 0.3]);
+    xlabel('Baudrate in GBd');
+     if i == 1
+        ylabel('BER')
+     end
+    beautifyBERplot()
+    set(gca, 'YScale', 'log');
+legend
+    subplot(1,4,4)
+    hold on
+    if m == 4
+
+        plot(bitrate*1e-9,ber_db(i,:),'DisplayName',sprintf('Diff. Code + DB tgt.'),'Color',cols(i,:),'LineStyle','--','HandleVisibility','on','Marker','diamond');
+
+    elseif m == 6
+
+        plot(bitrate*1e-9,ber_vnle(i,:),'DisplayName',sprintf('VNLE + PF + MLSE'),'Color',cols(i,:),'LineStyle','-','HandleVisibility','on','Marker','o');
+        % plot(bitrate*1e-9,ber_mlse(i,:),'DisplayName',sprintf('MLSE',m),'Color',cols(i,:),'LineStyle',':','HandleVisibility',hv,'Marker','square');
+
+    elseif m ==8
+
+        plot(bitrate*1e-9,ber_vnle(i,:),'DisplayName',sprintf('Tx precomp + VNLE'),'Color',cols(i,:),'LineStyle','-','HandleVisibility','on','Marker','o');
+        % plot(bitrate*1e-9,ber_mlse(i,:),'DisplayName',sprintf('MLSE',m),'Color',cols(i,:),'LineStyle',':','HandleVisibility',hv,'Marker','square');
+
+    end
+    yline(4.85e-3,'HandleVisibility','off');
+    yline(2e-2,'HandleVisibility','off');
+    xticks(bitrate_ticks);
+    xlim([min(bitrate_ticks) max(bitrate_ticks)]);
+    ylim([1e-4 0.3]);
+    xlabel('Gross Bitrate in Gbps');
+    % ylabel('BER')
+    beautifyBERplot()
+    set(gca, 'YScale', 'log');
+
+
+end
+
+
 
 figure()
 title(sprintf('%d km | 1310 nm | PAM %d | VNLE',uloops.link_length,uloops.M));

projects/IMDD_base_system/imdd_model.m

@@ -1,4 +1,6 @@
-function  [output] = imdd_model(simulation_mode,varargin)
+function  [output] = imdd_model(varargin)
+
+simulation_mode = 0;
 
 %%% Change folder
 curFolder = pwd;
@@ -17,6 +19,9 @@ fdac            = 256e9;
 fadc            = 256e9;
 random_key      = 1;
 
+interference_attenuation = 0;
+is_mpi          = 1;
+
 precomp         = 0;
 db_precode      = 0;
 
@@ -35,7 +40,7 @@ tx_bw_nyquist   = 0.8;
 link_length     = 1;
 
 % RX
-rop = -8;
+rop = -5;
 rx_bw_nyquist = 0.8;
 
 vnle_order1 = 50;
@@ -45,6 +50,7 @@ vnle_order3 = 7;
 vnle_order=[vnle_order1,vnle_order2,vnle_order3];
 dfe_order = [0 0 0];
 
+pf_ncoeffs = 1;
 
 alpha = 0;
 
@@ -54,6 +60,7 @@ mu_ffe1 = 0.0001;
 mu_ffe2 = 0.0008;
 mu_ffe3 = 0.001;
 mu_dc = 0.005;
+% mu_dc = 0;
 
 mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
 mu_dfe = 0.0004;
@@ -61,7 +68,7 @@ mu_dfe = 0.0004;
 
 dfe_ = sum(dfe_order)>0;
 
-doub_mode = db_mode.db_precoded;
+doub_mode = db_mode.no_db;
 
 %%% change specific parameter if given in varargin
 % Parse optional input arguments
@@ -132,10 +139,15 @@ f_nyquist       = fsym/2;
 %%% run the simulation or measurement or ...
 if simulation_mode
 
-    Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"rrcalpha",rcalpha);
+    Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
+    rcalpha = 1;
+    Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
 
+    db_precode = 0;
+    db_encode = 0;
+    apply_pulsef = 1;
     [Digi_sig,Symbols,Tx_bits] = PAMsource(...
-        "fsym",fsym,"M",M,"order",17,"useprbs",1,...
+        "fsym",fsym,"M",M,"order",18,"useprbs",0,...
         "fs_out",fdac,...
         "applyclipping",0,"clipfactor",1.5,...
         "applypulseform",apply_pulsef,"pulseformer",Pform,...
@@ -143,7 +155,9 @@ if simulation_mode
         "db_precode",db_precode,"db_encode",db_encode,...
         "mrds_code",0,"mrds_blocklength",512).process();
 
-    % Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
+    Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
+
+
 
     %%%%% AWG
     % El_sig = M8199A("kover",kover).process(Digi_sig);
@@ -207,7 +221,7 @@ else
         'fiber_length',     link_length, ...
         'interference_attenuation', [], ...
         'interference_path_length', [], ...
-        'is_mpi',           0, ...
+        'is_mpi',           is_mpi, ...
         'pam_level',        M, ...
         'precomp_amp',      [], ...
         'rop_attenuation',  0, ...
@@ -218,7 +232,8 @@ else
         );
 
     selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
-        'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','Measurements.power_rop','Configurations.v_bias'};
+        'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','Measurements.power_rop','Configurations.v_bias',...
+        'Configurations.interference_attenuation'};
 
     [dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
     [~, uniqueIdx] = unique(dataTable.run_id);  % Get unique run_id indices
@@ -236,13 +251,14 @@ else
     
 
     % Raw_signal = load([basePath, char(dataTable.rx_raw_path(1))]);
+    % Raw_signal.Scpe_sig_raw.plot("displayname",'0db atten','fignum',10101)
     % Raw_signal = Raw_signal.Scpe_sig_raw;
     % 
     % Raw_signal = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.55,"fs",Raw_signal.fs,"filterType",filtertypes.gaussian,"active",true).process(Raw_signal);
     % 
-    Scpe_cell{1}.eye(fsym,M,"displayname",'eye','fignum',227);
+    % Scpe_cell{1}.eye(fsym,M,"displayname",'eye','fignum',227);
     % 
-    % Raw_signal.spectrum("normalizeTo0dB",0,"fignum",336,"fft_length",2^12);
+    % Raw_signal.spectrum("normalizeTo0dB",0,"fignum",11,"fft_length",2^12);
     % Raw_signal.move_it_spectrum("fignum",334);
     % Raw_signal.move_it_spectrum("fignum",334);
 
@@ -261,7 +277,7 @@ dbtgt_package = {};
 
 
 proc_occ = min(1,length(Scpe_cell));
-for occ = 1:proc_occ
+for occ = 1%:proc_occ
 
     Scpe_sig = Scpe_cell{occ};
 
@@ -269,11 +285,18 @@ for occ = 1:proc_occ
     Scpe_sig =  Scpe_sig.resample("fs_out",2*fsym);
 
     %%%%%% Sync Rx signal with reference %%%%%%
-    % [Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym);
+    [Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym);
 
     Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
 
     Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
+    % 
+    % Pform = Pulseformer("fsym",Scpe_sig.fs,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha,"matched",0);
+    % 
+    % Scpe_sig_matched = Pform.process(Scpe_sig);
+    % 
+    % Scpe_sig.spectrum("normalizeTo0dB",0,"fignum",336,"displayname","scope ");
+    % Scpe_sig_matched.spectrum("normalizeTo0dB",0,"fignum",336,"displayname","matched");
 
     %%% EQUALIZING
            
@@ -283,15 +306,17 @@ for occ = 1:proc_occ
             % eq_mlse     = FFE_DCremoval("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0,"dc_buffer_len",512,"mu_dc",0.05);
             
             mu_ffe = [mu_ffe1 mu_ffe2 mu_ffe3];
+            vnle_order=[vnle_order1,vnle_order2,vnle_order3];
 
             % %%%%% VNLE + DFE %%%%
-            if 1
-                eq_vnle_dfe     = EQ("Ne",vnle_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",1,"ideal_dfe",0);
+            if 0
                 
-                [result] = vnle(eq_vnle_dfe,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",doub_mode,"showAnalysis",1);
+                eq_vnle_dfe     = EQ("Ne",vnle_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
+                eq_2 = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0);
+                
+                [result] = vnle(eq_vnle_dfe,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",doub_mode,"showAnalysis",1,"postFFE",[]);
                 vnle_dfe_package{occ} = result;
 
-
             end
             %%%%% VNLE + PF + MLSE %%%%
             if 1
@@ -299,7 +324,7 @@ for occ = 1:proc_occ
                 % len_tr = length(Symbols)-1000;
                 eq_vnle_    = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
                 % eq_vnle_ = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0,"order",vnle_order,"sps",2,"decide",0);
-                pf_         = Postfilter("ncoeff",1,"useBurg",1);
+                pf_         = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
                 mlse_       = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
     
                 [result] = vnle_postfilter_mlse(eq_vnle_,pf_,mlse_,M,Scpe_sig,Symbols,Tx_bits,"precode_mode",doub_mode,'showAnalysis',1);
@@ -314,7 +339,7 @@ for occ = 1:proc_occ
                 mlse_db = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
                 eq_db = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
 
-                [result] = duobinary_target(eq_db, mlse_db, M, Scpe_sig, Symbols, Tx_bits, "precode_mode", doub_mode,'showAnalysis',1);
+                [result] = duobinary_target(eq_db, mlse_db, M, Scpe_sig, Symbols, Tx_bits, "precode_mode", doub_mode,'showAnalysis',0);
                 dbtgt_package{occ} = result;
                 
 

projects/Lab_2024/offline_dsp_analysis/load_n_plot_transfer_characteristic.m

@@ -1,7 +1,7 @@
 
 
-precomp_path = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\standard_system";
-precomp_filename = "lab_mpi_setup_2";
+precomp_path = "C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\precomp";
+precomp_filename = "lab_high_speed";
 
 freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
 freqresp.load('loadPath',precomp_path,'fileName',precomp_filename);

projects/Messung_Zürich/change_filenames.m

@@ -0,0 +1,85 @@
+%% 1) Read all files in the TR folder
+pathToTimingRecov = "C:\Users\Silas\Documents\MATLAB\Datensätze\IEF_Polariton_2025\36_IMDD_Kiel\Data\TR_ZIP";
+trFiles = dir(fullfile(pathToTimingRecov, 'TR_SILAS_*.mat'));
+
+%% Directory for measurement files (used to extract metadata)
+pathToMeasurement = "C:\Users\Silas\Documents\MATLAB\Datensätze\IEF_Polariton_2025\36_IMDD_Kiel\Data\20250221";
+
+%% Initialize lists for different PAM types
+listPAM2 = {};
+listPAM4 = {};
+listPAM6 = {};
+listPAM8 = {};
+
+%% Loop over each TR file
+for k = 1:length(trFiles)
+    % Get current TR file name
+    trFileName = trFiles(k).name;
+    
+    % 2) Extract file code from TR file name.
+    % For a filename like "TR_SILAS_20250221T001800.mat" the code is "20250221T001800".
+    filecode = extractBetween(trFileName, 'TR_SILAS_', '.mat');
+    
+    % Find corresponding measurement file by code (custom function)
+    measurementFilename = findFileByCode(pathToMeasurement, filecode{1});
+    
+    % 3) Extract parameters from the measurement filename using regex.
+    % Expected measurement filename format (example): 
+    % "Pmod_-10p000dBm_P_PD_-20p000dBm_..._32GBd_4PAM__1234T5678"
+    tokens = regexp(measurementFilename, ...
+        'Pmod_([-0-9p]+)dBm_P_PD_([-0-9p]+)dBm_.*?_(\d+)GBd_(\d+)PAM__\d+T\d+', ...
+        'tokens');
+    if isempty(tokens)
+        error('Filename format not recognized for measurement file: %s', measurementFilename);
+    end
+    tokens = tokens{1};
+    
+    % Convert token strings to numbers
+    config.P_laser = str2double(strrep(tokens{1}, 'p', '.'));
+    config.P_pd    = str2double(strrep(tokens{2}, 'p', '.'));
+    config.fsym    = str2double(tokens{3}) * 1e9; % Convert from GBd to Hz
+    config.M       = str2double(tokens{4});
+    
+    % Display loaded metadata
+    fprintf('Loaded measurement file: %s\n', measurementFilename);
+    fprintf('P_laser: %.3f dBm\n', config.P_laser);
+    fprintf('P_pd: %.3f dBm\n', config.P_pd);
+    fprintf('fsym: %.1f GBd\n', config.fsym * 1e-9);
+    fprintf('M: %d\n', config.M);
+    
+    % 4) Rename the TR file to include the metadata.
+    % New filename format: TR_SILAS_<code>_Pmod_<P_laser>dBm_P_PD_<P_pd>dBm_<fsym in GBd>GBd_<M>PAM.mat
+    newTRname = sprintf('TR_SILAS_%s_Pmod_%.3fdBm_P_PD_%.3fdBm_%dGBd_%dPAM', ...
+                        filecode{1}, config.P_laser, config.P_pd, config.fsym/1e9, config.M);
+
+    newTRname = strrep(newTRname,'.','p');
+    newTRname = [newTRname, '.mat'];
+    movefile(fullfile(pathToTimingRecov, trFileName), fullfile(pathToTimingRecov, newTRname));
+    
+    % Append the file code to the corresponding PAM list based on config.M
+    switch config.M
+        case 2
+            listPAM2{end+1} = filecode{1};
+        case 4
+            listPAM4{end+1} = filecode{1};
+        case 6
+            listPAM6{end+1} = filecode{1};
+        case 8
+            listPAM8{end+1} = filecode{1};
+        otherwise
+            warning('Unexpected PAM value %d in file %s', config.M, measurementFilename);
+    end
+end
+
+%% Display the lists of file codes for each PAM type
+disp('List of file codes for PAM2:');
+disp(listPAM2);
+
+disp('List of file codes for PAM4:');
+disp(listPAM4);
+
+disp('List of file codes for PAM6:');
+disp(listPAM6);
+
+disp('List of file codes for PAM8:');
+disp(listPAM8);

projects/Messung_Zürich/dsp_all_files.m

@@ -0,0 +1,366 @@
+
+M = 6;
+if M == 2
+    file_codes = {'20250221T035221'	'20250221T035354'	'20250221T035824'	'20250221T035931'	'20250221T040035'	'20250221T040132'	'20250221T040226'	'20250221T040523'	'20250221T040646'	'20250221T040723'	'20250221T040843'	'20250221T041011'	'20250221T041101'	'20250221T041244'};
+elseif M == 4
+    file_codes = {'20250221T030844'	'20250221T032043'	'20250221T032312'	'20250221T032424'	'20250221T032529'	'20250221T032632'	'20250221T032800'	'20250221T033035'	'20250221T033138'	'20250221T033246'	'20250221T033425'	'20250221T033527'	'20250221T033642'	'20250221T033743'	'20250221T033851'	'20250221T034314'	'20250221T034529'	'20250221T034647'	'20250221T034756'	'20250221T034915'};
+elseif M == 6
+    file_codes = {'20250221T041445'	'20250221T041512'	'20250221T041539'	'20250221T041607'	'20250221T041633'	'20250221T041702'	'20250221T041729'	'20250221T041758'	'20250221T041825'	'20250221T041854'	'20250221T041922'	'20250221T041951'	'20250221T042019'	'20250221T042048'	'20250221T042117'	'20250221T042147'	'20250221T042215'};
+elseif M ==8
+    file_codes = {'20250221T004926'	'20250221T023534'	'20250221T024256'	'20250221T024629'	'20250221T024929'	'20250221T025305'	'20250221T025505'	'20250221T025856'	'20250221T030122'	'20250221T030311'	'20250221T030513'};
+end
+
+if 0
+    uloops          = struct;
+    uloops.filecode = file_codes;
+    uloops.vnle_order1 = [50];
+    uloops.vnle_order2 = [5];
+    uloops.vnle_order3 = [5];
+    wh = DataStorage(uloops);
+    wh.addStorage("ber");
+
+    wh = submit_handle(@dsp_ief_file,wh,"parallel",1);
+end
+
+if 0
+    % Bring figure(5) to focus
+    fig = figure(2);
+
+    % Get handles to all line objects in the figure
+    lines = findobj(fig, 'Type', 'line');
+
+    % Preallocate cell arrays to store the data for each line
+    xData = cell(numel(lines),1);
+    yData = cell(numel(lines),1);
+
+    % Loop through each line and extract its data
+
+    for k = 1:numel(lines)
+        xData{k} = get(lines(k), 'XData');
+        yData{k} = get(lines(k), 'YData');
+    end
+
+    ief.M2.baudr_new = xData{4};
+    ief.M2.ngmi_new = yData{4};
+
+    ief.M4.baudr_new = xData{3};
+    ief.M4.ngmi_new = yData{3};
+
+    ief.M6.baudr_new = xData{2};
+    ief.M6.ngmi_new = yData{2};
+
+    ief.M8.baudr_new = xData{1};
+    ief.M8.ngmi_new = yData{1};
+
+    ief.M2.ber_new = yData{4};
+    ief.M4.ber_new = yData{3};
+    ief.M6.ber_new = yData{2};
+    ief.M8.ber_new = yData{1};
+
+    pam2_baudr = xData{4};
+    pam2_ber = yData{4};
+    pam2_ngmi = yData{4};
+
+    pam4_baudr = xData{3};
+    pam4_ber = yData{3};
+    pam4_ngmi = yData{3};
+
+    pam6_baudr = xData{2};
+    pam6_ber = yData{2};
+    pam6_ngmi = yData{2};
+
+    pam8_baudr = xData{1};
+    pam8_ber = yData{1};
+    pam8_ngmi = yData{1};
+
+    pam2_baudr_lowdsp = xData{4};
+    pam2_ber_lowdsp = yData{4};
+    pam2_ngmi_lowdsp = yData{4};
+
+    pam4_baudr_lowdsp = xData{3};
+    pam4_ber_lowdsp = yData{3};
+    pam4_ngmi_lowdsp = yData{3};
+
+    pam6_baudr_lowdsp = xData{2};
+    pam6_ber_lowdsp = yData{2};
+    pam6_ngmi_lowdsp = yData{2};
+
+    pam8_baudr_lowdsp = xData{1};
+    pam8_ber_lowdsp = yData{1};
+    pam8_ngmi_lowdsp = yData{1};
+
+
+
+end
+
+
+close all
+figure(1)
+cnt = 1;
+for M = [2,4,6,8]
+    % for i = 1:numel(uloops.vnle_order2)
+    % for j = 1:numel(uloops.vnle_order3)
+    wh = eval(sprintf('wh_pam%d',M));
+    a =wh.getStoValue('ber',wh.parameter.filecode.values, wh.parameter.vnle_order1.values, wh.parameter.vnle_order2.values,wh.parameter.vnle_order3.values);
+    % a =wh_mit_1001.getStoValue('ber',uloops.filecode, wh_mit_1001.parameter.vnle_order1.values, wh_mit_1001.parameter.vnle_order2.values,wh_mit_1001.parameter.vnle_order3.values);
+    baudrate = cell2mat(cellfun(@(a) a.config.fsym,  a, 'UniformOutput', false));
+    [baudrate, idx] = sort(baudrate);
+
+    % get best results per baudrate
+    vnle = 0;
+    try
+        ber_vnle_values = cellfun(@(a) cellfun(@(y) y.ber_vnle, a.vnle_package, 'UniformOutput', false), a, 'UniformOutput', false);
+        ber_vnle_infrate = cellfun(@(a) cellfun(@(y) y.inf_rate_vnle, a.vnle_package, 'UniformOutput', false), a, 'UniformOutput', false);
+
+        best_vnle = cellfun(@(x) min(cell2mat(x)), ber_vnle_values);
+        best_vnle = best_vnle(idx);
+        best_gmi_vnle = cellfun(@(x) min(cell2mat(x)), ber_vnle_infrate);
+        best_gmi_vnle = best_gmi_vnle(idx);
+
+        % netRateVNLE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'NGMI',best_gmi_vnle./log2(M), 'BER',best_vnle);
+
+        vnle = 1;
+    end
+
+    mlse = 0;
+    try
+        ber_vnle_values = cellfun(@(a) cellfun(@(y) y.ber_vnle, a.vnle_pf_package, 'UniformOutput', false), a, 'UniformOutput', false);
+        best_vnle_2 = cellfun(@(x) min(cell2mat(x)), ber_vnle_values);
+        best_vnle_2 = best_vnle_2(idx);
+
+        gmi_vnle_values = cellfun(@(a) cellfun(@(y) y.gmi, a.vnle_pf_package, 'UniformOutput', false), a, 'UniformOutput', false);
+        best_gmi_vnle = cellfun(@(x) min(cell2mat(x)), gmi_vnle_values);
+        best_gmi_vnle = best_gmi_vnle(idx);
+
+        ber_mlse_values = cellfun(@(a) cellfun(@(y) y.ber_mlse, a.vnle_pf_package, 'UniformOutput', false), a, 'UniformOutput', false);
+        best_mlse = cellfun(@(x) min(cell2mat(x)), ber_mlse_values);
+        best_mlse = best_mlse(idx);
+
+        if M == 8
+            best_vnle_2(2) = [];
+            best_mlse(2) = [];
+            best_gmi_vnle(2) = [];
+            best_db(2) = [];
+
+            baudrate(2) = [];
+        elseif M == 4
+             
+        end
+
+        mlse = 1;
+    end
+
+    db = 0;
+    try
+        ber_db_values = cellfun(@(a) cellfun(@(y) y.ber, a.dbtgt_package, 'UniformOutput', false), a, 'UniformOutput', false);
+        best_db = cellfun(@(x) min(cell2mat(x)), ber_db_values);
+        best_db = best_db(idx);
+        if M == 4
+            best_db(end-1:end) = [];
+            baudrate(end-1:end) = [];
+        end
+
+        db = 1;
+    end
+
+    %% BER PLOT
+
+    % figure(1)
+    subplot(1,2,1)
+    cols = cbrewer2('Set1',6);
+    hold on
+    title(sprintf('BER'));
+    % title(sprintf('%d 1st order',uloops.vnle_order1(i)));
+    xax = baudrate.*1e-9;
+
+    if M == 4 || M == 2
+        plot(xax,best_db,'DisplayName',sprintf('PAM %d | DB+MLSE',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        plot(ief.(sprintf('M%d', M)).baudr_new,ief.(sprintf('M%d', M)).ber_new,'DisplayName',sprintf('PAM %d |VNLE',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+    elseif M == 6
+        plot(xax,best_vnle_2,'DisplayName',sprintf('PAM %d |VNLE',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        
+        % plot(ief.(sprintf('M%d', M)).baudr_new,ief.(sprintf('M%d', M)).ber_new,'DisplayName',sprintf('PAM %d |VNLE',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+       
+    else
+        % plot(xax,best_vnle_2,'DisplayName',sprintf('PAM %d |VNLE',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+     
+        plot(ief.(sprintf('M%d', M)).baudr_new,ief.(sprintf('M%d', M)).ber_new,'DisplayName',sprintf('PAM %d |VNLE',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+    end
+
+    if 0
+        if vnle
+            plot(xax,best_vnle,'DisplayName',sprintf('VNLE'),'Color',cols(2,:),'LineStyle','-','HandleVisibility','on');
+        end
+        if mlse
+            plot(xax,best_vnle_2,'DisplayName',sprintf('VNLE'),'Color',cols(2,:),'LineStyle','-','HandleVisibility','on');
+            plot(xax,best_mlse,'DisplayName',sprintf('VNLE + 1 tap post-filter + MLSE'),'Color',cols(3,:),'LineStyle','-','HandleVisibility','on');
+        end
+        if db
+            plot(xax,best_db,'DisplayName',sprintf('DB tgt. + MLSE'),'Color',cols(1,:),'LineStyle','-','HandleVisibility','on');
+        end
+
+        plot(ief.(sprintf('M%d', M)).baudr,ief.(sprintf('M%d', M)).ber,'DisplayName',sprintf('VNLE [100,15,15] (ETH)'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+        plot(ief.(sprintf('M%d', M)).baudr_lowdsp,ief.(sprintf('M%d', M)).ber_lowdsp,'DisplayName',sprintf('VNLE [100,15,15] (ETH)'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+    end
+
+    set(gca, 'YScale', 'log');
+    ylim([1e-6 0.3]);
+    xlim([92, 260 ]);
+    xticks([0:16:280]);
+    yline([4.85e-3, 2e-2],'HandleVisibility','off');
+    % legend
+    % beautifyBERplot()
+    xlabel('baudrate in GBd');
+    ylabel('BER');
+    set(findall(gca, '-property', 'Interpreter'), 'Interpreter', 'latex');
+
+    set(gcf, 'Color', 'w');
+    set(gca, 'Box', 'on', 'LineWidth', 0.8);  % Thicker border
+    grid on;
+    set(gca, 'FontSize', 10, 'FontName', 'Times New Roman');
+    %
+
+    %% NGMI PLOT
+
+    % figure(2)
+    % cols = cbrewer2('Set1',6);
+    % hold on
+    % title(sprintf('%d km ; %.1f nm ; PAM %d',1,1313,M));
+    % xax = baudrate.*1e-9;
+    %
+    % plot(xax,best_gmi_vnle./log2(M),'DisplayName',sprintf('NGMI VNLE'),'Color',cols(2,:),'LineStyle','-','HandleVisibility','on');
+    %
+    % plot(ief.(sprintf('M%d', M)).baudr,ief.(sprintf('M%d', M)).ngmi,'DisplayName',sprintf('VNLE [100,15,15] (ETH)'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+    % plot(ief.(sprintf('M%d', M)).baudr_lowdsp,ief.(sprintf('M%d', M)).ngmi_lowdsp,'DisplayName',sprintf('VNLE [100,15,15] (ETH)'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+    %
+    % set(gca, 'YScale', 'log');
+    % ylim([0.7 1]);
+    % xlim([min(xax), max(xax) ]);
+    % xticks(xax);
+    % yline([0.8],'HandleVisibility','off');
+    % legend
+    % beautifyBERplot()
+    % xlabel('Baudrate in GBd');
+    % ylabel('NGMI');
+
+    %% AIR Plot
+    % subplot(1,3,2)
+    %
+    % netRateMLSE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'BER',best_mlse);
+    % netRateVNLE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'NGMI',best_gmi_vnle./log2(M), 'BER',best_vnle_2);
+    % netRateDB   = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'BER',best_db);
+    %
+    % netRateIEF = TransmissionPerformance().calculateNetRate(log2(M)*ief.(sprintf('M%d', M)).baudr,'BER',ief.(sprintf('M%d', M)).ber,'NGMI',ief.(sprintf('M%d', M)).ngmi);
+    % netRateIEF_lowdsp = TransmissionPerformance().calculateNetRate(log2(M)*ief.(sprintf('M%d', M)).baudr_lowdsp,'BER',ief.(sprintf('M%d', M)).ber_lowdsp,'NGMI',ief.(sprintf('M%d', M)).ngmi_lowdsp);
+    %
+    % cols = cbrewer2('Set1',8);
+    % hold on
+    % title(sprintf('AIR'));
+    % xax = baudrate.*1e-9;
+    %
+    % if M == 2 || M == 4
+    %
+    %     % plot(xax,netRateMLSE.HD.NetRate.*1e-9,'DisplayName',sprintf('MLSE - HD'),'Color',cols(1,:),'LineStyle',':','HandleVisibility','on');
+    %     % plot(xax,netRateVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('VNLE SD+HD'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+    %     plot(xax,netRateDB.HD.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE HD',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on');
+    %     plot(xax,netRateDB.O_FEC.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE O-FEC',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on');
+    %     % plot(xax,netRateDB.KP4_hamming.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE KP4-FEC',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on');
+    %
+    % else
+    %
+    %     % plot(xax,netRateMLSE.HD.NetRate.*1e-9,'DisplayName',sprintf('MLSE - HD'),'Color',cols(1,:),'LineStyle',':','HandleVisibility','on');
+    %     % plot(xax,netRateVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('VNLE SD+HD'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+    %     % plot(ief.(sprintf('M%d', M)).baudr,netRateIEF.HD.NetRate,'DisplayName',sprintf('PAM %d | HD IEF',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on');
+    %     plot(ief.(sprintf('M%d', M)).baudr,netRateIEF.SDHD.NetRate,'DisplayName',sprintf('PAM %d | SD+HD IEF',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on');
+    %
+    % end
+    % set(gca, 'YScale', 'log');
+    % ylim([92 450]);
+    % xlim([min(xax), max(xax) ]);
+    % xlim([92, 260 ]);
+    % xticks([0:16:280]);
+    % yline([0.8],'HandleVisibility','off');
+    % legend
+    % beautifyBERplot()
+    % xlabel('Baudrate in GBd');
+    % ylabel('Net Rate in Gbps');
+    %
+    %
+
+
+    %% NDR PLOT
+
+    subplot(1,2,2)
+    netRateIEF = TransmissionPerformance().calculateNetRate(log2(M)*ief.(sprintf('M%d', M)).baudr,'BER',ief.(sprintf('M%d', M)).ber,'NGMI',ief.(sprintf('M%d', M)).ngmi);
+    netRateIEF_lowdsp = TransmissionPerformance().calculateNetRate(log2(M)*ief.(sprintf('M%d', M)).baudr_lowdsp,'BER',ief.(sprintf('M%d', M)).ber_lowdsp,'NGMI',ief.(sprintf('M%d', M)).ngmi_lowdsp);
+    netRateIEF_new = TransmissionPerformance().calculateNetRate(log2(M)*ief.(sprintf('M%d', M)).baudr_new,'BER',ief.(sprintf('M%d', M)).ber_new,'NGMI',ief.(sprintf('M%d', M)).ngmi_new);
+
+
+    cols = cbrewer2('Set1',8);
+    hold on
+    title(sprintf('Net Bitrate'));
+    xax = baudrate.*1e-9;
+
+    if M == 2 || M == 4
+
+        log2M = log2(M);
+
+        netRateDB   = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'BER',best_db);
+
+        % plot(xax,netRateMLSE.HD.NetRate.*1e-9,'DisplayName',sprintf('MLSE - HD'),'Color',cols(1,:),'LineStyle',':','HandleVisibility','on');
+        % plot(xax,netRateVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('VNLE SD+HD'),'Color',cols(4,:),'LineStyle','-','HandleVisibility','on');
+        plot(xax,netRateDB.HD.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE HD',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        
+        plot(xax,netRateDB.O_FEC.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE O-FEC',M),'Color',cols(M/2,:),'LineStyle','-.','HandleVisibility','on','Marker','x','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        % plot(xax,netRateDB.KP4_hamming.NetRate.*1e-9,'DisplayName',sprintf('PAM %d | DB+MLSE KP4-FEC',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','*','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+        plot(ief.(sprintf('M%d', M)).baudr_new,netRateIEF_new.SDHD.NetRate,'DisplayName',sprintf('PAM %d | SD+HD',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+        plot(ief.(sprintf('M%d', M)).baudr_new,ief.(sprintf('M%d', M)).ngmi_new.*ief.(sprintf('M%d', M)).baudr_new.*log2M ,'DisplayName',sprintf('PAM %d | AIR',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+
+    elseif M == 6
+
+        log2M = 2.5;
+        netRateMLSE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'BER',best_mlse);
+        netRateVNLE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'NGMI',best_gmi_vnle./log2(M), 'BER',best_vnle_2);
+
+        plot(xax,netRateVNLE.HD.NetRate.*1e-9,'DisplayName',sprintf('MLSE - HD'),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        plot(xax,netRateVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('VNLE SD+HD'),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+        % plot(ief.(sprintf('M%d', M)).baudr_new,netRateIEF_new.HD.NetRate,'DisplayName',sprintf('PAM %d | HD IEF',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        % plot(ief.(sprintf('M%d', M)).baudr_new,netRateIEF_new.SDHD.NetRate,'DisplayName',sprintf('PAM %d | SD+HD IEF',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+
+    else
+
+        log2M = log2(M);
+
+        netRateMLSE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'BER',best_mlse);
+        netRateVNLE = TransmissionPerformance().calculateNetRate(log2(M)*baudrate,'NGMI',best_gmi_vnle./log2(M), 'BER',best_vnle_2);
+
+        % plot(xax,netRateVNLE.HD.NetRate.*1e-9,'DisplayName',sprintf('MLSE - HD'),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        % plot(xax,netRateVNLE.SDHD.NetRate.*1e-9,'DisplayName',sprintf('VNLE SD+HD'),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+
+        plot(ief.(sprintf('M%d', M)).baudr_new,netRateIEF_new.HD.NetRate,'DisplayName',sprintf('PAM %d | HD IEF',M),'Color',cols(M/2,:),'LineStyle',':','HandleVisibility','on','Marker','square','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+        plot(ief.(sprintf('M%d', M)).baudr_new,netRateIEF_new.SDHD.NetRate,'DisplayName',sprintf('PAM %d | SD+HD IEF',M),'Color',cols(M/2,:),'LineStyle','-','HandleVisibility','on','Marker','o','MarkerFaceColor',[1,1,1],'MarkerEdgeColor',cols(M/2,:),'MarkerSize',4,'LineWidth',1.4);
+     
+    end
+    set(gca, 'YScale', 'log');
+    ylim([150 450]);
+    xlim([min(xax), max(xax) ]);
+    xlim([92, 270 ]);
+    xticks([0:16:280]);
+    yline([0.8],'HandleVisibility','off');
+    % legend
+
+    xlabel('Baudrate in GBd');
+    ylabel('Net Rate in Gbps');
+    set(findall(gca, '-property', 'Interpreter'), 'Interpreter', 'latex');
+
+    set(gcf, 'Color', 'w');
+    set(gca, 'Box', 'on', 'LineWidth', 0.8);  % Thicker border
+    grid on;
+    set(gca, 'FontSize', 10, 'FontName', 'Times New Roman');
+
+end

projects/Messung_Zürich/dsp_ief_file.m

@@ -0,0 +1,203 @@
+
+function [results] = dsp_ief_file(varargin)
+
+    mu_ffe1 = 0.0001;
+    mu_ffe2 = 0.0008;
+    mu_ffe3 = 0.001;
+    mu_dc = 0.0003; %0.0003;
+    
+    mu_dfe_training = 0.0004;
+    vnle_order1 = 50;
+    vnle_order2 = 3;
+    vnle_order3 = 3;
+
+    dfe_mu = 0.0005;
+    
+
+    tcorrect = 0;
+    %%% change specific parameter if given in varargin
+    % Parse optional input arguments
+    if ~isempty(varargin)
+        var_s = varargin{1};
+        if isstruct(var_s)
+            fields = fieldnames(var_s);
+            for i = 1:numel(fields)
+                if isnumeric(fields{i})
+                    eval([fields{i}, ' = ',  num2str( var_s.(fields{i}) ), ';']);
+                    fprintf("%s <-- %.2f \n", fields{i}, var_s.(fields{i}));
+                else
+                    eval([fields{i}, ' = ',  'var_s.(fields{',num2str(i),'})' , ';']);
+                end
+    
+            end
+        else
+            error('Optional variables should be passed as a struct.');
+        end
+    end
+    
+    pathToMeasurement = "C:\Users\Silas\Documents\MATLAB\Datensätze\IEF_Polariton_2025\36_IMDD_Kiel\Data\20250221";
+    filename    = findFileByCode(pathToMeasurement, filecode{1});
+
+    pathToTimingRecov = "C:\Users\Silas\Documents\MATLAB\Datensätze\IEF_Polariton_2025\36_IMDD_Kiel\Data\TR_ZIP";
+    filename_2    = findFileByCode(pathToTimingRecov, filecode{1});
+    
+    % Extract parameters from the filename using an updated regex
+    tokens = regexp(filename, 'Pmod_([-0-9p]+)dBm_P_PD_([-0-9p]+)dBm_.*?_(\d+)GBd_(\d+)PAM__\d+T\d+', 'tokens');
+    if isempty(tokens)
+        error('Filename format not recognized.');
+    end
+    
+    tokens = tokens{1};
+    
+    % Convert values
+    config.P_laser = str2double(strrep(tokens{1}, 'p', '.'));
+    config.P_pd = str2double(strrep(tokens{2}, 'p', '.'));
+    config.fsym = str2double(tokens{3}) * 1e9; % Convert GBd to Hz
+    config.M = str2double(tokens{4});
+    
+    % Display results
+    fprintf('Loaded file: %s\n', filename);
+    fprintf('P_laser: %.3f dBm\n', config.P_laser);
+    fprintf('P_pd: %.3f dBm\n', config.P_pd);
+    fprintf('fsym: %.1f GBd\n', config.fsym*1e-9);
+    fprintf('M: %d\n', config.M);
+    
+    %%% Load Data
+    filepath = fullfile(filename);
+    ief_ = h5info(filepath);
+    
+    config.fs_rx = h5readatt(filepath,'/','fs'); %sampling frequency at Rx
+    config.fs_tx = h5readatt(filepath, '/','fs_Tx'); %sampling frequency at Tx
+    config.fsym = h5readatt(filepath, '/','R'); %Baudrate
+    config.M = h5readatt(filepath, '/','M'); % PAM- 'M'
+    config.ROF = h5readatt(filepath, '/','ROF');
+    config.PulseShape =h5readatt(filepath, '/','PulseShape');
+    
+    yOrg = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YOrg');
+    yInc = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YInc');
+    
+    dataRx = double(h5read(filepath, '/Waveforms/Channel 2/Channel 2Data')); % rohdaten des CH4
+    bitsTx = h5read(filepath, '/Settings/dataTx'); %Binär
+
+    if config.M ~= 6
+        bitsTx = reshape(bitsTx,log2(config.M),[])';
+    else
+        %bitsTx = reshape(bitsTx,5,[])';
+    end
+
+    %%% Build Tx Signal (Bits, Pam Map, Symbols)
+    Tx_bits = Informationsignal(bitsTx);
+    Tx_symbols = PAMmapper(config.M,0,"eth_style",1).map(Tx_bits);
+    Tx_symbols.fs = config.fsym;
+
+    if 0
+        Rx_bits = PAMmapper(config.M,0,"eth_style",1).demap(Tx_symbols);
+        [~,~,ber_bw,~] = calc_ber(Rx_bits.signal,Tx_bits.signal(1:length(Rx_bits.signal)),"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+    end
+
+    %%% Build Rx Signal (Rx, normalize,remove mean)
+    loadAfterTR = 1;
+    if loadAfterTR 
+        if 1
+            rx_sig = load(filename_2);
+            rx_sig=rx_sig.signal_TR;
+            if config.M == 6
+                rx_sig_pam6 = zeros(length(rx_sig)*2,1);
+                rx_sig_pam6(1:2:end) = real(rx_sig);
+                rx_sig_pam6(2:2:end) = imag(rx_sig);
+                rx_sig = rx_sig_pam6;
+                Rx_Sig_resamp = Informationsignal(rx_sig,"fs",config.fsym);
+                % Tx_symbols.signal = Tx_symbols.signal(1:end/2);
+            else
+                Rx_Sig_resamp = Informationsignal(rx_sig,"fs",config.fsym*2);
+            end
+            
+        else
+            rx_sig = load(string(['testSilas_',char(filecode{1}),'.mat']),"signal_TR3");
+            rx_sig=rx_sig.signal_TR3;
+            Rx_Sig_resamp = Informationsignal(rx_sig,"fs",config.fsym*2);
+        end
+
+    else
+
+        dataRx = dataRx*yInc+yOrg;
+        Rx_Sig = Informationsignal(dataRx,"fs",config.fs_rx);
+    
+        Rx_Sig.signal = Rx_Sig.signal - mean(Rx_Sig.signal);
+    
+        Rx_Sig = Rx_Sig.normalize("mode","rms");
+
+        %%%%%% Sample to 2x fsym %%%%%%
+        Rx_Sig_resamp = Rx_Sig.resample("fs_out",config.fsym);
+
+    end
+   
+
+    %%%%%% Sync Rx signal with reference (S is a cell array with all occurences) %%%%%%
+
+    [~,S,isFlipped] = Rx_Sig_resamp.tsynch("reference",Tx_symbols,"fs_ref",config.fsym,"debug_plots",1);
+
+    output = struct();
+    vnle_package = {};
+    vnle_pf_package = {};
+    dbtgt_package = {};
+    
+    for s = 1%:length(S)
+        Rx_Sig_sync = S{s};
+        Rx_Sig_sync = Rx_Sig_sync.normalize("mode","rms");
+        Rx_Sig_sync = Rx_Sig_sync.resample("fs_out",2*config.fsym);
+
+        mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
+        vnle_order=[vnle_order1,vnle_order2,vnle_order3];
+        eq_    = EQ("Ne",vnle_order,"Nb",[0,0,0],"training_length",4096*4,"training_loops",4,"dd_loops",3,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe_training],"DFEmu",dfe_mu,"FFEmu",0,"plotfinal",0,"ideal_dfe",0,"plottrain",0);
+    
+       
+        %%%%% VNLE only (or DFE) %%%%
+        if 0
+
+             eq_post = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",1001,"sps",1,"decide",0);
+            [result] = vnle(eq_,config.M,Rx_Sig_sync,Tx_symbols,Tx_bits,"precode_mode",db_mode.no_db,"showAnalysis",1,'eth_style',1,'postFFE',eq_post);
+
+            netRate = TransmissionPerformance().calculateNetRate(log2(config.M)*config.fsym,'NGMI',result.inf_rate_vnle, 'BER',result.ber_vnle);
+            vnle_package{s} = result;
+
+        end
+    
+        %%%%% VNLE + PF + MLSE %%%%
+        if 1
+    
+            eq_post     = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",1001,"sps",1,"decide",0);
+            pf_         = Postfilter("ncoeff",1,"useBurg",1);
+            mlse_       = MLSE("duobinary_output",0,'M',config.M,'trellis_states',PAMmapper(config.M,0).levels);
+            mlse_       = MLSE_viterbi("duobinary_output",0,'M',config.M,'trellis_states',PAMmapper(config.M,0).levels);
+            doub_mode   = db_mode.no_db;
+    
+            [result] = vnle_postfilter_mlse(eq_,pf_,mlse_,config.M,Rx_Sig_sync,Tx_symbols,Tx_bits,"precode_mode",doub_mode,'showAnalysis',1,'eth_style_symbol_mapping',1,'postFFE',eq_post);
+            netRate = TransmissionPerformance().calculateNetRate(log2(config.M)*config.fsym,'NGMI',result.gmi./log2(config.M), 'BER',result.ber_mlse);
+            fprintf('VNLE SD: %.1f GBd \n',netRate.SDHD.NetRate.*1e-9);
+            fprintf('MLSE HD: %.1f GBd \n',netRate.HD.NetRate.*1e-9);
+
+            vnle_pf_package{s} = result;
+    
+        end
+    
+        %%%%% Duobinary Targeting %%%%
+        if 1
+    
+            mlse_db = MLSE_viterbi("DIR",[1,1],"duobinary_output",0,"M",config.M,"trellis_states",PAMmapper(config.M,0).levels);
+            doub_mode = db_mode.db_emulate;
+    
+            [result] = duobinary_target(eq_, mlse_db, config.M, Rx_Sig_sync, Tx_symbols, Tx_bits, "precode_mode", doub_mode,'showAnalysis',1,'eth_style_symbol_mapping',1);
+            dbtgt_package{s} = result;
+    
+        end
+    
+    end
+
+    results.vnle_package = vnle_package;
+    results.vnle_pf_package = vnle_pf_package;
+    results.dbtgt_package = dbtgt_package;
+    results.config = config;
+
+
+end

projects/Messung_Zürich/findFileByCode.m

@@ -0,0 +1,40 @@
+function fileName = findFileByCode(folderPath, code)
+% FINDFILEBYCODE Searches for a file in a folder structure by a given code.
+%   fileName = findFileByCode(folderPath, code) searches recursively in
+%   folderPath for a file containing 'code' in its name and returns the
+%   full file name if found.
+%
+%   Inputs:
+%       folderPath - The root directory to search in
+%       code       - The unique code to search for in file names
+%
+%   Output:
+%       fileName   - The full file name if found, empty if not found
+
+    % Initialize output
+    fileName = '';
+    
+    % Get list of all files and folders in the folderPath
+    files = dir(folderPath);
+    
+    % Iterate through the list
+    for i = 1:length(files)
+        % Skip '.' and '..'
+        if files(i).isdir
+            if ~startsWith(files(i).name, '.') % Avoid hidden folders
+                % Recursive search in subdirectories
+                subFolder = fullfile(folderPath, files(i).name);
+                fileName = findFileByCode(subFolder, code);
+                if ~isempty(fileName)
+                    return; % Stop searching if found
+                end
+            end
+        else
+            % Check if the file name contains the code
+            if contains(files(i).name, code)
+                fileName = fullfile(folderPath, files(i).name);
+                return;
+            end
+        end
+    end
+end

projects/Messung_Zürich/minimal_pam4_mlse.m

@@ -0,0 +1,19 @@
+
+
+mlse_sig_sd=load("imdd_simulation\projects\Messung_Zürich\mlse_sig_sd.mat","mlse_sig_sd");
+mlse_sig_sd = mlse_sig_sd.mlse_sig_sd;
+tx_symbols=load("imdd_simulation\projects\Messung_Zürich\tx_symbols.mat","tx_symbols");
+tx_symbols = tx_symbols.tx_symbols;
+
+mlse_       = MLSE_viterbi("duobinary_output",0,'M',4,'trellis_states',PAMmapper(4,0).levels);
+mlse_.DIR = [1.0000    0.5452];
+mlse_sig_sd = mlse_.process(mlse_sig_sd);
+
+
+% 
+% mlse_       = MLSE_viterbi("duobinary_output",0,'M',4,'trellis_states',PAMmapper(4,0).levels);
+% mlse_.DIR = [1.0000    0.5452];
+% mlse_sig_sd = mlse_.process(mlse_sig_sd,tx_symbols);
+
+h = [1.0000    0.5452];
+chatgpt_answer(mlse_sig_sd.signal,tx_symbols.signal,h)

projects/Messung_Zürich/submit_handle.m

@@ -0,0 +1,69 @@
+function wh = submit_handle(funcHandle, wh, options)
+
+arguments
+    funcHandle
+    wh 
+    options.parallel = 1;
+end
+
+%%% 2) SUBMIT SIMULATION
+% Initialize job results
+if options.parallel
+    curpool = gcp('nocreate');
+    if isempty(curpool)
+        parpool;
+    else
+        % stop all forgotten or unfetched jobs from queue
+        if ~isempty(curpool.FevalQueue.QueuedFutures) || ~isempty(curpool.FevalQueue.RunningFutures)
+            oldq = length(curpool.FevalQueue.QueuedFutures) + length(curpool.FevalQueue.RunningFutures);
+            curpool.FevalQueue.cancelAll
+            fprintf('Canceled %d unfetched jobs from old queue.', oldq);
+        end
+    end
+    results = parallel.FevalFuture.empty();
+else
+    results = [];
+end
+
+fprintf('Requested %d loops\n', wh.getLastLinIndice);
+
+for lin_idx = 1:wh.getLastLinIndice
+    optionalVars = struct();
+    
+    if ~isempty(wh.getDimension)
+        % Build the optionalVars struct
+        [parametervalues, parameternames] = wh.getPhysIndicesByLinIndex(lin_idx);
+        for pidx = 1:numel(parameternames)
+            optionalVars.(parameternames{pidx}) = parametervalues{pidx};
+        end
+    end
+
+    %%% SIMULATION HERE
+    if options.parallel
+        numOutputs = 1;
+        results(lin_idx) = parfeval(funcHandle, numOutputs, optionalVars);
+    else
+        finalresults{lin_idx} = feval(funcHandle, optionalVars);
+        wh.addValueToStorageByLinIdx(finalresults{lin_idx}, 'ber', lin_idx);
+    end
+end
+
+if options.parallel
+    %%% 4) Setup waitbar
+    h = waitbar(0, 'Processing Simulations...');
+    updateWaitbar = @(~) waitbar(mean(arrayfun(@(f) strcmp(f.State, 'finished'), results)), h);
+
+    fprintf('Fetching results... \n');
+    
+    updateWaitbarFutures = afterEach(results, updateWaitbar, 0);
+    afterAll(updateWaitbarFutures, @(~) delete(h), 0);
+
+    %%% 7) Fetch final results after all computations
+    fetchOutputs(results);
+
+    for ridx = 1:length(results)
+        wh.addValueToStorageByLinIdx(results(ridx).OutputArguments{1}, 'ber', ridx);
+    end
+end
+
+end

test/duobinary_minimal_example.m

@@ -1,11 +1,11 @@
 useprbs = 1;
-M = 6;
+M = 2;
 randkey = 1;
 datarate = 448e9;
 fsym = round(datarate / log2(M)) ;
 
 %%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
-O = 15; %O of prbs
+O = 16; %O of prbs
 N = 2^(O); %length of prbs
 [~,seed] = prbs(O,1); %initialize first seed of prbs
 bitpattern=[];
@@ -47,28 +47,79 @@ Tx_bits = Informationsignal(bitpattern);
 
 %%%%% Duobinary %%%%%%
 
+precode = 1;
+db_encode  = 0;
+
 close all
 Symbols_tx = PAMmapper(M,0).map(Tx_bits);
 Symbols_tx.fs = fsym;
 
-Symbols1 = Duobinary().precode(Symbols_tx);
-figure;histogram(Symbols1.signal);
+%%% precode
+if precode
+    Symbols0 = Duobinary().precode(Symbols_tx);
+else
+    Symbols0 = Symbols_tx;
+end
 
-Symbols2 = Duobinary().encode(Symbols1);
-figure;histogram(Symbols2.signal);
+figure;histogram(Symbols0.signal);
 
-Symbols3 = Duobinary().decode(Symbols2);
-figure;histogram(Symbols3.signal);
-autoArrangeFigures;
+for n = 0:200
 
-Rx_bits = PAMmapper(M,0).demap(Symbols3);
+    if db_encode 
+        Symbols1 = Duobinary().encode(Symbols0);
+    else
+        Symbols1 = Symbols0;
+    end
 
-%%%%% Check BER of Bit Sequence %%%%%%
+    Symbols2 = Symbols1;
+    pos = 1;
+    if n~=0
+        for pos = 1:n
+            po = randi(100);
+            a = Symbols2.signal(100+pos) == Symbols1.signal(100+po);
+            while a == 1
+                po = po+1;
+                po = randi(100);
+                a = Symbols2.signal(100+pos) == Symbols1.signal(100+po);
+            end
+             Symbols2.signal(100+pos) = Symbols1.signal(100+po);
+        end
+    end
 
-[~,error_num,ber,error_pos] = calc_ber(Tx_bits.signal,Rx_bits.signal,"skip_front",0,"skip_end",0,"returnErrorLocation",1);
+    % disp(Symbols2.signal(100:100+pos)==Symbols1.signal(100:100+pos))
     
-disp(['BER: ',sprintf('%.1E',ber),' - - PAM-',num2str(M)]);
-% 
+    %%% encode
+    
+    if db_encode 
+        
+        % figure;histogram(Symbols2.signal);
+        
+        Symbols3 = Duobinary().decode(Symbols2);
+        % figure;histogram(Symbols3.signal);
+        % autoArrangeFigures;
+    elseif precode 
+        Symbols3 = Duobinary().encode(Symbols2);
+        Symbols3 = Duobinary().decode(Symbols3);
+        % figure;histogram(Symbols3.signal);
+    else
+        Symbols3 = Symbols2;
+    end
+    
+    Rx_bits = PAMmapper(M,0).demap(Symbols3);
+    
+    %%%%% Check BER of Bit Sequence %%%%%%
+    
+    [~,error_num(n+1),ber,error_pos] = calc_ber(Tx_bits.signal,Rx_bits.signal,"skip_front",10,"skip_end",10,"returnErrorLocation",1);
+    
+    % disp(['BER: ',sprintf('%.1E',ber),sprintf(' - Num. Err: %.1d',error_num(n+1)-2),' - - PAM-',num2str(M)]);
+    fprintf('n: %d - Num. Err: %.1d \n',n,error_num(n+1));
+end
+
+
+figure()
+hold on
+scatter(1:length(Symbols3),Symbols3.signal,1,'.');
+scatter(error_pos,Symbols3.signal(error_pos),14,'o');
 
 
 figure(3);

test/matched_filter_minimal.m

@@ -0,0 +1,61 @@
+%%% Run parameters
+% TX
+M               = 4;
+fsym            = 32e9;
+
+apply_pulsef    = 1;
+fdac            = 256e9;
+fadc            = 256e9;
+random_key      = 1;
+
+precomp         = 0;
+db_precode      = 0;
+
+db_encode       = 0;
+
+rcalpha         = 0.05;
+kover           = 16;
+vbias_rel       = 0.5;
+u_pi            = 2.9;
+vbias           = -vbias_rel*u_pi;
+laser_wavelength    = 1293;
+laser_linewidth     = 0;
+tx_bw_nyquist   = 0.8;
+
+% 1) PRBS Generation
+O = 18; %order of prbs
+N = 2^(O-1); %length of prbs
+
+%%%%% MOVE-IT PRMS %%%%
+Mi_prms = Moveit_wrapper("prms");
+if M == 6
+    Mi_prms.para.bl = 2^(O-2);
+    Mi_prms.para.dimension = 5;
+else
+    Mi_prms.para.bl = 2^(O-1);
+    Mi_prms.para.dimension = log2(M); %2.5bits/sym -> 2 bit/sym
+end
+Mi_prms.para.rand = 0;
+Mi_prms.para.order = floor(O / log2(M));
+Mi_prms.para.skip =0;
+Mi_prms.para.bruijn = 0;
+Mi_prms.para.reset_prms = 0;
+Mi_prms.para.method = 1;
+bitpattern = Mi_prms.process([]);
+if M == 6
+    bitpattern = reshape(bitpattern',[],1);
+    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
+end
+
+bits = Informationsignal(bitpattern);
+
+symbols = PAMmapper(M,0).map(bits);
+symbols.fs = fsym;
+
+Pform       = Pulseformer("fsym",fsym,"fs",fsym,"alpha",0.6,"pulse","rrc","pulselength",64,"matched_sps",4,"output_sps",2);
+Pform.process(symbols);
+
+MF = Pulseformer("fsym",fsym,"fdac",fdac,"pulse","rrc","pulselength",1024,"alpha",rcalpha,"matched",0);
+Digi_sig = MF.process(Digi_sig);
+
+Digi_sig.spectrum("displayname",'Signal after shaping','fignum',1);

test/test_mapping_eth.m

@@ -0,0 +1,39 @@
+
+% Setup PRBS parameters
+O = 6;
+M = 6;
+N = 2^(O-1); % Length of PRBS
+randkey = 1; % Random key for random stream
+use_eth_mapping =1;
+
+if M ~= 6
+    dimension = log2(M);
+else
+    dimension = 5;
+end
+
+[~, seed] = prbs(O, 1); % Initialize first seed of PRBS
+bitpattern = [];
+
+s = RandStream('twister', 'Seed', randkey);
+for i = 1:dimension
+    bitpattern(:, i) = randi(s, [0 1], N, 1);
+end
+if M == 6
+    bitpattern = reshape(bitpattern',[],1);
+    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
+end
+
+Tx_bits = Informationsignal(bitpattern);
+
+Digi_Mod = PAMmapper(M, 0,"eth_style",use_eth_mapping);
+
+% Map bits to symbols
+Symbols = Digi_Mod.map(Tx_bits);
+
+% Demap symbols back to bits
+Rx_bits = Digi_Mod.demap(Symbols);
+
+[~, error_num, ber, ~] = calc_ber(Tx_bits.signal(1:length(Rx_bits.signal)), Rx_bits.signal,"skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
+
+fprintf('BER: %.1E \n',ber);