Additions:

- Correction of the weighted DFE function in EQ.m
- Some evaluation scripts for FSO Data

Classes/00_signals/Signal.m

@@ -172,9 +172,9 @@ classdef Signal
 
             hold on;
             if isempty(options.color)
-                plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', '.', 'LineStyle','none', 'MarkerSize', 0.1);
+                plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', 'none', 'LineStyle','-', 'MarkerSize', 0.1);
             else
-                plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', '.', 'LineStyle','none', 'MarkerSize', 0.1,'Color',options.color);
+                plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', 'none', 'LineStyle','-', 'MarkerSize', 0.1,'Color',options.color);
             end
             % 2 c)
             % - xlabel if not already here: time in readable format (1 ms and not 1e-3 s)

Classes/04_DSP/Equalizer/EQ.m

@@ -10,10 +10,12 @@ classdef EQ < handle
         training_length %Number of training symbols
         training_loops %Number of loops through sequence for training mode
         ideal_dfe %Error free DFE decisions
-        weighted_DFE %Weighted DFE on/off
+        weighted_DFE %Weighted DFE off (0)/on (1)/PDFE (2)
         weighted_DFE_mode %Weighted DFE mode
         weighted_DFE_d_min %d_min threshold parameter for weighted DFE mode 1
         weighted_DFE_I_mode %[a_s, b_s, I_max]-parameters for the weighted DFE
+        PDFE_coefficient %Coefficient for PDFE
+        weighted_error %error based on hard- or weighted decision
 
         DB_aim %Aim at duobinary output sequence
 
@@ -43,7 +45,6 @@ classdef EQ < handle
 
         save_taps
 
-
         %during simulation
         k0
         b
@@ -76,6 +77,8 @@ classdef EQ < handle
                 options.weighted_DFE_mode = 'R1';
                 options.weighted_DFE_d_min = 0.5;
                 options.weighted_DFE_I_mode = [5,0.5,0.6];
+                options.PDFE_coefficient = 0.5;
+                options.weighted_error = 0; %0: Error based on hard-decision. 1: Error based on weighted decision.
 
                 options.DB_aim %Aim at duobinary output sequence
 
@@ -243,19 +246,11 @@ classdef EQ < handle
                     cnt = 1;
                     m = obj.k0+1; % starting symbol index at the delay compared to the training sequence
 
-                   
-
-                    % n => index in rx data sequence
-                    %Step From:  Oversampling(=2) * Startdelay + 1
-                    %Step Width: Oversampling(=2)
-                    %Step To:    Oversampling(=2) * Training Length
                     for n = obj.K*obj.k0+1:obj.K:obj.K*obj.training_length
 
                         % m => index in reference sequence
                         m = m+1;
 
-                        % 
-                        %dc_ = mean(data(obj.Ne(1)+n+(obj.K-1):-1:n+obj.K).');
                         % cut symbols from rx data sequence
                         X_1 = data(obj.Ne(1)+n+(obj.K-1):-1:n+obj.K).';
 
@@ -275,8 +270,6 @@ classdef EQ < handle
 
                         error = e_dc + e_ffe - e_dfe - ref_in(m-obj.k0);
 
-                        %error = e_dc + e_.'*input_vec - b_.'*reference_vec  - ref_in(m-obj.k0);     
-                        
                         if real(obj.FFEmu)
                             if obj.l1act
                                 sgn_e = e_;
@@ -297,28 +290,13 @@ classdef EQ < handle
 
                         e_dc = e_dc - obj.DCmu*error;
 
-                        % obj.error_log.e_ffe(cnt,trainloops) = e_ffe;
-                        % obj.error_log.e_dfe(cnt,trainloops) = e_dfe;
-                        % obj.error_log.e_(cnt,trainloops) = error;
-
                         cnt = cnt+1;
                         if obj.Nb(1) > 0
                             b_ = b_ + obj.DFEmu*error*reference_vec; % Seems like normalized DFE has worse performance
                         end
-
-%                         figure(111);stem((e_),'Markersize',2);ylim([-1 1]);title('FFE Filter Taps');
-% 
-%                         figure(222);
-%                         stem(input_vec);ylim([-3 3]);
-%                         hold on;
-%                         stem(reference_vec);ylim([-3 3]);
-%                         yline(error,'LineWidth',2); title('Input Vector');
-%                         hold off
-
                     end
                 end
 
-
                 %%
                 % Plot the intermediate coefficients after training mode
                 obj.b = b_(1:obj.Nb(1));
@@ -349,10 +327,8 @@ classdef EQ < handle
                     subplot(2,3,6);stem(obj.b3,'Markersize',2);
                     title('DFE coeff nl 3rd')
                     xlabel('coefficient index'); ylabel('value'); set(gca,'Fontsize',12)
-                    %set(gcf,'Position',[200 500 700 400])
                 end
 
-
                 if obj.l1act
                     neg_lin = find(abs(obj.e) < obj.thres(1));
                     neg_2nd = find(abs(obj.e2) < obj.thres(2));
@@ -401,6 +377,7 @@ classdef EQ < handle
                     cnt = 1;
                     m = 0;
                     output_vec = zeros(1,floor(length(data_in)/obj.K)); % initilaization of the output vector
+                    output_vec_weighted = zeros(size(output_vec));
                     dd_DFE = zeros(obj.Nb(1),1);
                     D_2 = zeros(Nb2,1);
                     D_3 = zeros(Nb3,1);
@@ -418,7 +395,6 @@ classdef EQ < handle
                     if obj.load_decisions
                         pathn = evalin('base','modeldir');
                         temp = load([pathn, 'MLSE_out', '.mat']) ;
-                        %eval(['dd_out_vals = temp.', 'a', ';']) ;
                         dd_out_vals=temp.a;
                         dd_out = zeros(size(data_in));
                         dd_out(1:2:length(data_in)) = dd_out_vals;
@@ -440,79 +416,103 @@ classdef EQ < handle
                         end
 
                         output_vec(m) = e_dc + input_vec.'*coeff;
+                        y_raw = output_vec(m);   % ungeweighteter Equalizer-Ausgang
 
                         if ~obj.load_decisions
                             [~,dd_idx] = min(abs(output_vec(m) - constellation_in_)); % decision for closest constellation point
                             dd_out(k) = constellation_in_(dd_idx);
                         end
 
-                        % Implementation of a weighted DFE in
+                        % ---------- WDFE / PDFE ----------
-                        % order to prevent error propagation.
+                        fb_sym = dd_out(k);
-                        % For further details, study [1], chapter 3.2.2 -
-                        % Modifications of DFE
 
-                        if obj.weighted_DFE
+                        if obj.weighted_DFE ~= 0
-                            % define new constellations
+                            % Get constellation
-                            const = unique(ref_in);
+                            const = obj.constellation_in;
 
-                            % determine reliability factor gamma_k
+                            % Half minimum symbol distance (for normalization of |x - xhat|)
+                            const_s = sort(const(:).');
+                            d = diff(const_s);
+                            dmin = min(d(d>0));
+                            halfStep = dmin/2;
+
+                            % Reliability gamma_k
                             if output_vec(m) > min(const) && output_vec(m) < max(const)
-                                gamma_k = 1 - abs(output_vec(m) - dd_out(k));
+                                gamma_k = 1 - abs(output_vec(m) - dd_out(k))/halfStep;
+                                gamma_k = max(0, min(1, gamma_k));  % clamp to [0,1]
                             else
                                 gamma_k = 1;
                             end
 
-                            % select mode
+                            % f(gamma_k)
-                            if strcmp(obj.weighted_DFE_mode,'R1')
+                            if obj.weighted_DFE == 1
-                                if gamma_k >= obj.weighted_DFE_d_min
+                                switch obj.weighted_DFE_mode
-                                    f_gamma_k = 1;
+                                    case 'R1'
-                                else
+                                        f_gamma_k = double(gamma_k >= obj.weighted_DFE_d_min);
-                                    f_gamma_k = 0;
+
-                                end
+                                    case 'R2'
-                            elseif strcmp(obj.weighted_DFE_mode,'R2')
                                         f_gamma_k = gamma_k;
-                            elseif strcmp(obj.weighted_DFE_mode,'I1')
+
-                                nom = 1-exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
+                                    case 'I1'
-                                denom = 1+exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
+                                        a_s = obj.weighted_DFE_I_mode(1);
-                                f_gamma_k = (1/2)*((nom/denom) - 1);
+                                        b_s = obj.weighted_DFE_I_mode(2);
-                            elseif strcmp(obj.weighted_DFE_mode,'I2')
+                                        t = a_s*((gamma_k/b_s) - 1);
-                                nom = 1-exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
+                                        f_gamma_k = 0.5*(tanh(t) + 1);
-                                denom = 1+exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
+
-                                f_gamma_k = (obj.weighted_DFE_I_mode(3)/2)*((nom/denom) - 1);
+                                    case 'I2'
+                                        a_s = obj.weighted_DFE_I_mode(1);
+                                        b_s = obj.weighted_DFE_I_mode(2);
+                                        Imax = obj.weighted_DFE_I_mode(3);
+                                        t = a_s*((gamma_k/b_s) - 1);
+                                        f_gamma_k = (Imax/2)*(tanh(t) + 1);
+
+                                    otherwise
+                                        error('Unknown weighted_DFE_mode');
                                 end
-                            % calculate weighted output
+
-                            output_vec(m) = f_gamma_k.*dd_out(k)+(1-f_gamma_k).*output_vec(m);
+                                % Weighted decision
+                                xbar = f_gamma_k*dd_out(k) + (1 - f_gamma_k)*output_vec(m);
+
+                            elseif obj.weighted_DFE == 2
+                                % PDFE
+                                xbar = obj.PDFE_coefficient*dd_out(k) + (1 - obj.PDFE_coefficient)*output_vec(m);
+                            end
+
+                            output_vec_weighted(m) = xbar;
+                            fb_sym = xbar;
+                            output_vec(m) = xbar;
                         end
 
                         if obj.Nb(1) > 0
                             dd_DFE(2:end) = dd_DFE(1:end-1);
-                            dd_DFE(1) = dd_out(k);
+                            dd_DFE(1) = fb_sym;
 
                             if obj.ideal_dfe && m > obj.k0
                                 dd_DFE(1) = ref_in(m-obj.k0);
                             end
-                            [D_2,D_3] = obj.calc_nl_vecs(dd_DFE,ind_mat_DFE_2nd,ind_mat_DFE_3rd,norm_fac_DFE2,norm_fac_DFE3,delta_DFE2,delta_DFE3,cplx);
+
+                            [D_2,D_3] = obj.calc_nl_vecs(dd_DFE,ind_mat_DFE_2nd,ind_mat_DFE_3rd,...
+                                norm_fac_DFE2,norm_fac_DFE3,delta_DFE2,delta_DFE3,cplx);
+                        end
+
+                        if obj.weighted_DFE ~= 0 && obj.weighted_error
+                            % Error weighted decision
+                            error = y_raw - output_vec(m);
+                        else
+                            % Error hard decision
+                            error = y_raw - dd_out(k);
                         end
-                        %                     if dd_loop ~= 21
-                        error = output_vec(m) - dd_out(k);
-                        %                     else
-                        %                         error = 0;
-                        %                     end
 
                         coeff = coeff - mu_mat*error*conj(input_vec);
-                        %                     e_save(:,save_ind) = coeff;
-                        %                     save_ind = save_ind+1;
 
-                        if 1%mu_mat ~= 0
+                        if 1 % mu_mat ~= 0
                             e_dc = e_dc - obj.DCmu*error;
-                             % error_log(cnt,dd_loop) = e_dc;
                             cnt = cnt+1;
                         end
 
                     end
                 end
 
-                %figure(2023);plot(error_log(:,1))
                 % shifting the output sequence by k0 symbols
                 yout = (circshift(output_vec.',-(obj.k0))).'; %(circshift(dd_out.',-(obj.k0))).';
 
@@ -581,12 +581,6 @@ classdef EQ < handle
 
                 % save frequency response to the work space
                 if obj.save_taps
-                    % save the FFE coefficients to the work space
-                    % pathn = evalin('base','modeldir');
-                    % eval([obj.field_ffe, ' = obj.e ;']) ;
-                    % eval([obj.field_dfe, ' = b ;']) ;
-                    % eval(['save(''', pathn, '\',obj.filen,''', ''', obj.field_ffe,''', ''',obj.field_dfe,''') ;']) ;
-
                     save("coefficients",obj.e, obj.b);
                 end
 
@@ -726,19 +720,11 @@ classdef EQ < handle
 
                     ind_mat_3rd2 = NaN(N3,3);
                     count = 1;
-                    %         for t = 1:Ne3
-                    %             ind_mat_3rd2(count,:) = [t t t];
-                    %             count = count + 1;
-                    %         end
                     for t = 1:Ne3
-                        %             ind_mat_3rd2(count,:) = [t t t];
-                        %             count = count + 1;
                         for u = t:min(Ne3,t+len_3rd)
                             for v = unique([t u])
                                 ind_mat_3rd2(count,:) = [t v u];
                                 count = count + 1;
-                                %                     ind_mat_3rd2(count,:) = [t u u];
-                                %                     count = count + 1;
                             end
                         end
                     end
@@ -785,5 +771,5 @@ classdef EQ < handle
 end
 
 % References
-% [1] T. J. Wettlin, “Experimental Evaluation of Advanced Digital Signal Processing for Intra-Datacenter Systems using Direct-Detection,” 2023. [Online]. Available: https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2023-00703-8
+% [1] T. J. Wettlin, “Experimental Evaluation of Advanced Digital Signal Processing for Intra-Datacenter Systems using Direct-Detection,” 2023.
-
+%     [Online]. Available: https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2023-00703-8

Classes/04_DSP/Equalizer/ML_MLSE.m

@@ -621,7 +621,8 @@ classdef ML_MLSE < handle
 
             % --- Initialize weights
             if isempty(obj.w) || any(size(obj.w) ~= [obj.Nf+1,obj.nFeasible])
-                obj.w = randn(obj.Nf+1,obj.nFeasible);
+                % obj.w = randn(obj.Nf+1,obj.nFeasible);
+                obj.w = zeros(obj.Nf+1,obj.nFeasible);
             end
 
             % --- Fast lookup tables

Classes/04_DSP/Timing_Recovery.m

@@ -1,6 +1,7 @@
 classdef Timing_Recovery < handle
 
     properties(Access=public)
+        modulation
         timing_error_detector
         sps
         damping_factor
@@ -12,6 +13,7 @@ classdef Timing_Recovery < handle
         function obj = Timing_Recovery(options)
             arguments(Input)
 
+                options.modulation = 'PAM/PSK/QAM'
                 options.timing_error_detector = 'Gardner';
                 options.sps = 2;
                 options.damping_factor = 1.0;
@@ -32,6 +34,7 @@ classdef Timing_Recovery < handle
         function [data_out,timing_error] = process(obj, data_in)
 
             timing_synchronization = comm.SymbolSynchronizer( ...
+                "Modulation",          obj.modulation, ...
                 "TimingErrorDetector", obj.timing_error_detector, ...
                 "SamplesPerSymbol",    obj.sps, ...
                 "DampingFactor",       obj.damping_factor, ...

Functions/EQ_structures/ml_mlse.m

@@ -101,11 +101,11 @@ switch precode_mode
         tx_bits_precoded = mapper.demap(tx_symbols_precoded);
         
         rx_bits = mapper.demap(eq_signal_hd_precoded);
-        [~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
+        [~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 150, "skip_end", 150, "returnErrorLocation", 1);
         
         % B) Just determine BER
         rx_bits = mapper.demap(eq_signal_hd);
-        [bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
+        [bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 150, "skip_end", 150, "returnErrorLocation", 1);
         
     case db_mode.db_precoded
         % Data is precoded on TX side

projects/FSO_transmission/Evaluation Scripts/Optimize_WDFE_Parameters.m

@@ -0,0 +1,35 @@
+%%
+current = 225:10:285;
+current = string(current);
+power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
+power = string(power);
+num_pf_coeff = 4;
+taps_ffe = [300, 0, 0];
+taps_dfe = [2, 0, 0];
+M = 4;
+trlength = 4096*4;
+x = 225:10:285;
+BER_PAM_4 = [];
+filter_length = 210;
+eq_method = 2;
+num_signal_sweep = 11;
+our_signal = 1;
+
+idx = 4;
+
+obj = @(x) first_analysis_ber( ...
+    current(idx), power(idx), num_pf_coeff, taps_ffe, taps_dfe, ...
+    M, trlength, eq_method, filter_length, num_signal_sweep, our_signal, x);
+
+x0 = [1 0.1 0.1];
+lb = [1 0 0];
+ub = [10 1 1];
+
+opts = optimoptions('fmincon', ...
+    'Display','iter', ...
+    'Algorithm','sqp', ...
+    'MaxFunctionEvaluations', 500, ...
+    'StepTolerance', 1e-3, ...
+    'OptimalityTolerance', 1e-3);
+
+[xbest, berbest] = fmincon(obj, x0, [], [], [], [], lb, ub, [], opts);

projects/FSO_transmission/Evaluation Scripts/evalscript_cell.m

@@ -0,0 +1,38 @@
+%%
+current = 225:10:285;
+current = string(current);
+power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
+power = string(power);
+curr_pow_num = 4;
+num_pf_coeff = 4;
+taps_ffe = [300, 0, 0];
+taps_dfe = [0, 0, 0];
+M = 4;
+trlength = 4096*4;
+eq_method = 2;
+filter_length = 210;
+our_signal = 0;
+BER_vec = [];
+
+for i = 1:15
+    BER_value = first_analysis_ber(current(curr_pow_num), power(curr_pow_num), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, i, our_signal);
+    BER_vec = [BER_vec, BER_value];
+end
+
+%%
+BER_Our_Signal = [1.2e-3,1.3e-3,9.0e-4,3.8e-4,4.8e-4,4.8e-4,5.7e-4,4.1e-4,4.8e-4,5.6e-4,3.8e-4,4.1e-4,4.1e-4,5.2e-4,3.8e-4];
+BER_Their_Signal = [5.7e-4,4.0e-4,5.2e-4,4.9e-4,5.2e-4,5.5e-4,4.8e-4,4.0e-4,3.6e-4,4.6e-4,5.7e-4,5.3e-4,4.5e-4,5.9e-4,6.4e-4];
+
+figure;
+x = 1:15;
+plot(x, BER_Our_Signal, 'Marker', 'o', 'LineWidth', 1.75)
+hold on
+plot(x, BER_Their_Signal, 'Marker', 'o', 'LineWidth', 1.75)
+title('BER for FFE+PF+VNLE', 'Interpreter', 'latex')
+xlabel('Cell Entry', 'Interpreter', 'latex')
+ylabel('BER', 'Interpreter', 'latex')
+legend('Our Signal', 'Their Signal', 'Interpreter', 'latex')
+grid('minor')
+xlim([0 16])
+ylim([3e-4, 1.5e-3])
+hold off

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_2.m

@@ -11,24 +11,28 @@ trlength = 4096*2;
 x = 225:10:285;
 BER_PAM_2 = [];
 post_only = 0;
+filter_length_vec = 140;
+num_signal = 11;
+our_signal = 1;
 
-for eq_method = 2:4
+for eq_method = 1:4
 
     if ~post_only
         for j = 1:length(current)
-            BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method);
+            BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length_vec, num_signal, our_signal);
             BER_PAM_2 = [BER_PAM_2, BER_run];
         end
 
-        save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_2_' + string(eq_method) + '.mat', 'x', 'BER_PAM_2')
     end
+    save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_' + string(eq_method) + '.mat', 'x', 'BER_PAM_2')
+    BER_PAM_2 = [];
     
 end
 
 %%
 x = 225:10:285;
 for k = 1:4
-    BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_2_' + string(k) + '.mat');
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_' + string(k) + '.mat');
     BER = BER.BER_PAM_2;
     
     figure(202120)
@@ -50,10 +54,10 @@ legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
        'Location','southwest', 'FontSize', 14)
 
 % FEC Labels direkt im Plot
-text(280,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
-text(280,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(221,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
-text(280,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(221,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
-text(280,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+text(231,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
 
 xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
 ylabel('BER', 'Interpreter','latex')

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_2_opt.m

@@ -0,0 +1,74 @@
+%%
+current = 225:10:285;
+current = string(current);
+power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
+power = string(power);
+num_pf_coeff = 4;
+taps_ffe = [200, 0, 0];
+taps_dfe = [0, 0, 0];
+M = 2;
+trlength = 4096*2;
+x = 225:10:285;
+BER_PAM_2 = [];
+BER_num_signal_sweep = [];
+BER_num_signal_sweep_matrix = [];
+post_only = 0;
+filter_length = 140;
+our_signal = 1;
+idx_opt = [];
+
+for eq_method = 1:4
+    for j = 1:length(power)
+        for num_signal_sweep = 1:15
+            BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal_sweep, our_signal);
+            BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
+        end
+        [BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
+        BER_PAM_2 = [BER_PAM_2, BER_opt];
+        idx_opt = [idx_opt, num_signal_opt];
+        BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
+        BER_num_signal_sweep = [];
+    end
+    save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(eq_method) + '.mat', 'BER_PAM_2', 'BER_num_signal_sweep_matrix', 'idx_opt')
+    BER_PAM_2 = [];
+    idx_opt = [];
+end
+
+%%
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(k) + '.mat');
+    BER_values = BER.BER_PAM_2;
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+old_BER = [-1.5, -1.75, -2, -2.3, -2.6, -2.25, -1.95];
+old_BER = 10.^(old_BER);
+plot(x, old_BER, '-o','LineWidth',1.75)
+
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
+       'Interpreter','latex', ...
+       'Location','northwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
+ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
+% title('BER for PAM-4', 'Interpreter','latex')
+
+grid minor
+ylim([1e-4 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4.m

@@ -5,34 +5,37 @@ power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
 power = string(power);
 num_pf_coeff = 4;
 taps_ffe = [300, 0, 0];
-taps_dfe = [5, 0, 0];
+taps_dfe = [0, 0, 0];
 M = 4; 
 trlength = 4096*4;
 x = 225:10:285;
 BER_PAM_4 = [];
+filter_length = 210;
+num_signal = 11;
+our_signal = 1;
 
 for eq_method = 2
     for j = 4
-        BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method);
+        BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal);
         BER_PAM_4 = [BER_PAM_4, BER_run];
+        save_and_append('meineDB.sqlite', 'BER_PAM_4_Save_and_Append', eq_method, num_signal, BER_run, x)
     end
-    save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_4_DFE_' + string(eq_method) + '.mat', 'x', 'BER_PAM_4')
     BER_PAM_4 = [];
 end
 
 %%
-x = 225:10:285;
+x = 0:5:40;
-for k = 1:4
+for k = 2
-    BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_4_' + string(k) + '.mat');
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_DFE_Tap_Sweep_' + string(k) + '.mat');
-    BER = BER.BER_PAM_4;
+    BER_values = BER.BER_PAM_4;
     
     figure(202120)
-    plot(x, BER, '-o','LineWidth',1.75);
+    plot(x, BER_values, '-o','LineWidth',1.75);
     hold on
 end
-old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
+% old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
-old_BER = 10.^(old_BER);
+% old_BER = 10.^(old_BER);
-plot(x, old_BER, '-o','LineWidth',1.75)
+% plot(x, old_BER, '-o','LineWidth',1.75)
 
 h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
 h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
@@ -42,16 +45,16 @@ h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
 % Legende NUR für Kurven
 legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
        'Interpreter','latex', ...
-       'Location','southwest', 'FontSize', 14)
+       'Location','northwest', 'FontSize', 14)
 
 % FEC Labels direkt im Plot
-text(286,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
-text(285,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
-text(282.5,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
-text(287,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
 
-xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
-ylabel('BER', 'Interpreter','latex')
+ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
 % title('BER for PAM-4', 'Interpreter','latex')
 
 grid minor

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_baud_rate_sweep.m

@@ -10,20 +10,22 @@ trlength = 4096*4;
 x = 4:1:8;
 BER_PAM_4 = [];
 Alpha_PAM_4 = [];
+filter_length = 210;
+num_signal = 11;
 
 for method = 1:4
-    for i = 1:5
+    for i = 1:length(power)
-        [BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(i), power(i), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method);
+        [BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(i), power(i), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal);
         BER_PAM_4 = [BER_PAM_4, BER_run];
         % Alpha_PAM_4 = [Alpha_PAM_4, Alpha_run];
     end
-    save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\New Baud Rate Sweep Data\BER_PAM_4_' + string(method) + '.mat', 'x', 'BER_PAM_4')
+    save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_' + string(method) + '.mat', 'x', 'BER_PAM_4')
     BER_PAM_4 = [];
 end
 
 %% BER
 for k = 1:4
-    BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\New Baud Rate Sweep Data\BER_PAM_4_' + string(k) + '.mat');
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_' + string(k) + '.mat');
     BER = BER.BER_PAM_4;
     % x = BER.x;
     % BER_Alpha = load(filename);

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_baud_rate_sweep_opt.m

@@ -0,0 +1,88 @@
+baud_rate = 4:1:8;
+baud_rate = string(baud_rate);
+power = [8.4, 8.4, 42.3, 8.4, 8.4];
+power = string(power);
+num_pf_coeff = 4;
+taps_ffe = [300, 0, 0];
+taps_dfe = [0, 0, 0];
+M = 4;
+trlength = 4096*4;
+x = 4:1:8;
+BER_PAM_4 = [];
+BER_num_signal_sweep = [];
+BER_num_signal_sweep_matrix = [];
+Alpha_PAM_4 = [];
+filter_length = 210;
+idx_opt = [];
+
+for method = 1:4
+    for j = 1:length(power)
+        for num_signal_sweep = 1:15
+            [BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal_sweep);
+            BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
+            % Alpha_PAM_4 = [Alpha_PAM_4, Alpha_run];
+        end
+        [BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
+        BER_PAM_4 = [BER_PAM_4, BER_opt];
+        idx_opt = [idx_opt, num_signal_opt];
+        BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
+        BER_num_signal_sweep = [];
+    end
+    save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(method) + '.mat', 'BER_PAM_4', 'BER_num_signal_sweep_matrix', 'idx_opt')
+    BER_PAM_4 = [];
+end
+
+%% BER
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(k) + '.mat');
+    BER = BER.BER_PAM_4;
+    % x = BER.x;
+    % BER_Alpha = load(filename);
+    % BER = BER_Alpha.BER_PAM_4;
+    
+    % close all
+    figure(239)
+    plot(x, BER, '-o','LineWidth',1.75)
+    hold on
+end
+
+% old_BER = [-4.4, -4, -3.3, -2.7, -2.5, -2.475];
+% old_BER = 10.^(old_BER);
+% plot(x, old_BER, '--o','LineWidth',1)
+
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE','FFE+PF+MLSE','DB','ML-MLSE',...
+       'Interpreter','latex', ...
+       'Location','southwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(8.2,2.3e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(8.2,3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(8.2,5.6e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(8.2,2.5e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
+ylabel('BER', 'Interpreter','latex')
+% title('BER for PAM-4', 'Interpreter','latex')
+
+grid minor
+% ylim([1e-4 5e-2])
+xlim([3 9])
+set(gca,'YScale','log')
+hold off
+
+%% Channel Alpha
+% Alpha = BER_Alpha.Alpha_PAM_4;
+% figure
+% plot(x, Alpha, '--o','LineWidth',1)
+% hold on
+% xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
+% ylabel('Channel Alpha', 'Interpreter','latex')
+% title('Channel Alpha for PAM-4 - 300-Tap-FFE - 1 Postfilter Coefficients - 8192 Training Symbols', 'Interpreter','latex')
+% grid minor
+% hold off

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_opt.m

@@ -0,0 +1,73 @@
+%%
+current = 225:10:285;
+current = string(current);
+power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
+power = string(power);
+num_pf_coeff = 4;
+taps_ffe = [300, 0, 0];
+taps_dfe = [0, 0, 0];
+M = 4;
+trlength = 4096*4;
+x = 225:10:285;
+BER_PAM_4 = [];
+BER_num_signal_sweep = [];
+BER_num_signal_sweep_matrix = [];
+filter_length = 210;
+our_signal = 1;
+idx_opt = [];
+
+for eq_method = 1:4
+    for j = 1:length(power)
+        for num_signal_sweep = 1:15
+            BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal_sweep, our_signal);
+            BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
+        end
+        [BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
+        BER_PAM_4 = [BER_PAM_4, BER_opt];
+        idx_opt = [idx_opt, num_signal_opt];
+        BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
+        BER_num_signal_sweep = [];
+    end
+    save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(eq_method) + '.mat', 'BER_PAM_4', 'BER_num_signal_sweep_matrix', 'idx_opt')
+    BER_PAM_4 = [];
+    idx_opt = [];
+end
+
+%%
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(k) + '.mat');
+    BER_values = BER.BER_PAM_4;
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+% old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
+% old_BER = 10.^(old_BER);
+% plot(x, old_BER, '-o','LineWidth',1.75)
+
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
+       'Interpreter','latex', ...
+       'Location','northwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
+ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
+% title('BER for PAM-4', 'Interpreter','latex')
+
+grid minor
+ylim([1e-4 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_saa.m

@@ -0,0 +1,64 @@
+%%
+current = 225:10:285;
+current = string(current);
+power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
+power = string(power);
+num_pf_coeff = 4;
+taps_ffe = [300, 0, 0];
+taps_dfe = [5, 0, 0];
+M = 4; 
+trlength = 4096*4;
+x = 225:10:285;
+BER_PAM_4 = [];
+filter_length = 210;
+num_signal = 11;
+our_signal = 1;
+
+for eq_method = 2
+    for j = 4
+        BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal);
+        BER_PAM_4 = [BER_PAM_4, BER_run];
+        save_and_append('FSO_DB.sqlite', 'BER_PAM_4_Save_and_Append', 0, eq_method, num_signal, BER_run, x, taps_ffe)
+    end
+    BER_PAM_4 = [];
+end
+
+%%
+x = 0:5:40;
+for k = 2
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Save_and_Append.mat');
+    BER_values = BER.BER_PAM_4;
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+% old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
+% old_BER = 10.^(old_BER);
+% plot(x, old_BER, '-o','LineWidth',1.75)
+
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
+       'Interpreter','latex', ...
+       'Location','northwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
+ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
+% title('BER for PAM-4', 'Interpreter','latex')
+
+grid minor
+ylim([1e-4 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/Evaluation Scripts/execution_script_optimal_signal_trace_selection_sweep.m

@@ -0,0 +1,3 @@
+run('evalscript_pam_2_opt')
+run('evalscript_pam_4_opt')
+run('evalscript_pam_4_baud_rate_sweep_opt')

projects/FSO_transmission/Evaluation Scripts/first_analysis_baud_rate_sweep.m

@@ -1,4 +1,4 @@
-function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method)
+function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal)
     %%
     close all
     base = "C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\Sweep Data\";
@@ -90,7 +90,7 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
     % timing sync -> at this point we still have no symbol timing recovery, we
     % try to do this with 2sps EQ!
     [~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
-    Rx_matched_1 = Rx_synced_cell{1};
+    Rx_matched_1 = Rx_synced_cell{num_signal};
     
     % Rx_Time_Rec = Rx_matched;
     % Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1);
@@ -172,18 +172,6 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
         % Channel_Alpha = mlse_results.metrics.Alpha;
 
     elseif method == 3
-        %% -------------------- ML-based MLSE (L=2) --------------------
-        ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
-            "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",80,"sps",sps, ...
-            "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
-    
-        [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
-        fprintf('ML-based MLSE:\n');
-        fprintf('My EQ: %.1e \n',ml_mlse_results.metrics.BER);
-        fprintf('Paper: %.1e \n \n',ber_in_paper);
-        BER = ml_mlse_results.metrics.BER;
-
-    elseif method == 4
         %% -------------------- DB target --------------------
         mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
         
@@ -197,6 +185,19 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
         fprintf('My EQ: %.1e \n',dbt_results.metrics.BER);
         fprintf('Paper: %.1e \n \n',ber_in_paper);
         BER = dbt_results.metrics.BER;
+
+    elseif method == 4
+        %% -------------------- ML-based MLSE (L=2) --------------------
+        ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
+            "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",filter_length,"sps",sps, ...
+            "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
+    
+        [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
+        fprintf('ML-based MLSE:\n');
+        fprintf('My EQ: %.1e \n',ml_mlse_results.metrics.BER);
+        fprintf('Paper: %.1e \n \n',ber_in_paper);
+        BER = ml_mlse_results.metrics.BER;
+        
     end
     Channel_Alpha = 0;
 end

projects/FSO_transmission/Evaluation Scripts/first_analysis_ber.m

@@ -1,4 +1,4 @@
-function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method)
+function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal, weighted_DFE)
     %%
     close all
 
@@ -12,9 +12,11 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
     if M == 2
         tx_data_path = fullfile(base, "14G_PAM2\tx_info\tx_info_PAM2_14Gbd0.75RRC.mat");
         filename = fullfile(base, "14G_PAM2\M=2_Rs=1.4e10_Fs=8e10_I=" + current + "mA_RoP=" + power + "mW_L=31m_PS=RRC_rolloff=0.75_Mode=Rise.mat");
+        data_tr_mf = load("C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\FSO_FP_QCL_60umUTC\Already Recovered and Filtered\AfterSync_M=2_Rs=1.4e10_Fs=8e10_I=265mA_RoP=46.3mW_L=31m_PS=RRC_rolloff=0.75_Mode=Rise.mat");
     elseif M == 4
         tx_data_path = fullfile(base, "6G_PAM4\tx_info\tx_info_PAM4_6Gbd0.6RRC.mat");
         filename = fullfile(base, "6G_PAM4\M=4_Rs=6e9_Fs=8e10_I=" + current + "mA_RoP=" + power + "mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
+        data_tr_mf = load("C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\FSO_FP_QCL_60umUTC\Already Recovered and Filtered\AfterSync_M=4_Rs=6e9_Fs=8e10_I=255mA_RoP=42.3mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
     end
     
     if mode == 1
@@ -92,7 +94,11 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
     % timing sync -> at this point we still have no symbol timing recovery, we
     % try to do this with 2sps EQ!
     [~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
-    Rx_matched_1 = Rx_synced_cell{1};
+    Rx_matched_1 = Rx_synced_cell{num_signal};
+    
+    data_tr_mf = Electricalsignal(data_tr_mf.Results, "fs", fsym);
+    [~,Rx_synced_cell_tr_mf,inverted_tr_mf,sequenceFound_tr_mf,sequenceStarts_tr_mf] = data_tr_mf.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
+    Rx_tr_mf = Rx_synced_cell_tr_mf{num_signal};
 
     % Rx_Time_Rec = Rx_matched;
     % Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1);
@@ -106,13 +112,21 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
     end
     Rx_Time_Rec.fs = fsym;
 
+    Rx_Time_Rec = Rx_Time_Rec.normalize('mode','rms');
+    Rx_tr_mf = Rx_tr_mf.normalize('mode','rms');
+    
     % Rx_Time_Rec.signal = resample(Rx_Time_Rec.signal, 12e9, 6e9);
     
     % Rx_matched_1.plot("fignum",231231)
     % Rx_Time_Rec.plot("fignum",231231)
 
     %% not working.. 
+    if our_signal
         Rx_synced = Rx_Time_Rec;
+    else
+        Rx_synced = Rx_tr_mf;
+    end
+    % Rx_synced = Rx_Time_Rec;
     % Rx_synced = Rx_synced_cell{1};
     len_tr  = trlength;
     mu_ffe1 = 0.0001;
@@ -140,7 +154,7 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
     
         %% -------------------- FFE --------------------
         % requires some more digging what is going on :-) 
-        eq_ffe      = EQ("Ne",[500, 0, 0],"Nb",[0,0,0], ...
+        eq_ffe      = EQ("Ne",[500, 0, 0],"Nb",[0, 0, 0], ...
             "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
             "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
             "FFEmu",0,"plotfinal",0,"ideal_dfe",1);
@@ -162,7 +176,8 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
         eq_v        = EQ("Ne",taps_ffe,"Nb",taps_dfe, ...
             "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
             "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
-            "FFEmu",0,"plotfinal",0,"ideal_dfe",1);
+            "FFEmu",0,"plotfinal",0,"ideal_dfe",0,'weighted_DFE',1,'weighted_DFE_d_min',0.5, ...
+            'weighted_DFE_mode','I2','weighted_DFE_I_mode',weighted_DFE,'PDFE_coefficient',0.01);
         pf_         = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
         mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
         
@@ -194,7 +209,7 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
     
         %% -------------------- ML-based MLSE (L=2) --------------------
         ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
-            "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",80,"sps",1, ...
+            "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",filter_length,"sps",1, ...
             "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
     
         [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);

projects/FSO_transmission/Evaluation Scripts/first_analysis_tr_mf.m

@@ -98,7 +98,7 @@ H_transfer = Rx_spectrum.signal./Tx_spectrum.signal;
 H_inv = 1./H_transfer;
 
 %Number of Samples/Symbol after Matched Filter
-Kov = 14;
+Kov = 40;
 
 Scope_sig = Scope_sig.resample('fs_in',fs,'fs_out',Kov*fsym);
 
@@ -114,7 +114,7 @@ Rx_matched.spectrum("displayname",'Signal after matched filter','fignum',1);
 
 data_tr_mf = Electricalsignal(data_tr_mf.Results, "fs", fsym);
 [~,Rx_synced_cell_tr_mf,inverted_tr_mf,sequenceFound_tr_mf,sequenceStarts_tr_mf] = data_tr_mf.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
-Rx_tr_mf = Rx_synced_cell_tr_mf{1};
+Rx_tr_mf = Rx_synced_cell_tr_mf{11};
 
 % timing sync -> at this point we still have no symbol timing recovery, we
 % try to do this with 2sps EQ!
@@ -123,7 +123,7 @@ Rx_tr_mf = Rx_synced_cell_tr_mf{1};
 % Rx_matched = Rx_matched.resample("fs_out",2*fsym);
 
 [~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
-Rx_matched_1 = Rx_synced_cell{1};
+Rx_matched_1 = Rx_synced_cell{11};
 
 Rx_matched_original = Rx_synced_cell{1};
 Rx_matched_original.signal = resample(Rx_matched_original.signal,1,Kov);
@@ -135,14 +135,15 @@ Time_Rec = 1;
 if Time_Rec
     % [Rx_Time_Rec, Timing_Error] = Timing_Recovery("modulation", 'PAM/PSK/QAM', "timing_error_detector",'Gardner (non-data-aided)','sps',Kov,'damping_factor',1,'normalized_loop_bandwidth',1e-4,'detector_gain',2.7).process(Rx_matched_1);
 
-    % [Rx_Time_Rec, Timing_Error_MG] = Godard_Timing_Recovery('mode',3,'num_blocks',1,'fft_length',length(Rx_matched_1),'sps',Kov,'rolloff',0.6,'mu',-0.2,'Ki',1e-4).process(Rx_matched_1);
+    % [Rx_Time_Rec, Timing_Error_MG] = Godard_Timing_Recovery('mode',2,'num_blocks',1,'fft_length',length(Rx_matched_1),'sps',Kov,'rolloff',0.6,'mu',-0.2,'Ki',1e-4).process(Rx_matched_1);
     % Rx_Time_Rec = Rx_Time_Rec.resample('fs_in',Kov*fsym,'fs_out',fsym);
 
-    Rx_Time_Rec = MaxVar_Timing_Recovery('mode',0,'fsym',fsym,'fadc',Kov*fsym,'num_tau',Kov*128,'sps',Kov,'comp_signal',Rx_tr_mf,'comp_mode',0).process(Rx_matched_1);
+    Rx_Time_Rec = MaxVar_Timing_Recovery('mode',0,'fsym',fsym,'fadc',Kov*fsym,'num_tau',Kov*2048,'sps',Kov,'comp_signal',Rx_tr_mf,'comp_mode',0).process(Rx_matched_1);
     
     sps = 1;
 else
     Rx_Time_Rec = Rx_matched_1;
+
     sps = 1;
 end
 
@@ -188,7 +189,7 @@ for our_signal = 1
     end
     % Rx_synced = Rx_Time_Rec;
     % Rx_synced = Rx_synced_cell{1};
-    len_tr  = 4096*2;
+    len_tr  = 4096*4;
     mu_ffe1 = 0.0001;
     mu_ffe2 = 0.0008;
     mu_ffe3 = 0.001;
@@ -232,40 +233,41 @@ for our_signal = 1
     % end
     
     %% -------------------- VNLE + MLSE --------------------
-    % pf_ncoeffs  = 4;
+    pf_ncoeffs  = 4;
-    % eq_v        = EQ("Ne",[300, 0, 0],"Nb",[0, 0, 0], ...
+    eq_v        = EQ("Ne",[300, 0, 0],"Nb",[2, 0, 0], ...
-    %     "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
+        "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
-    %     "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
+        "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
-    %     "FFEmu",0,"plotfinal",0,"ideal_dfe",1, ...
+        "FFEmu",0,"plotfinal",0,"ideal_dfe",0, ...
-    %     'weighted_DFE',0,'weighted_DFE_d_min',0.5,'weighted_DFE_mode','R2','weighted_DFE_I_mode',[5,0.5,0.6]);
+        'weighted_DFE',1,'weighted_DFE_d_min',0.5,'weighted_DFE_mode','I2','weighted_DFE_I_mode',[1,0.1,0.1], ...
-    % % eq_v = FFE_DFE('ffe_order',300,'dfe_order',5,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5, ...
+        'PDFE_coefficient',0.01);
-    % %     'ffe_mu_dd',mu_ffe,'ffe_mu_tr',0,'dfe_mu_dd',mu_dfe,'dfe_mu_tr',0.005,'sps',sps,'decide',0);
+    % eq_v = FFE_DFE('ffe_order',300,'dfe_order',5,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5, ...
-    % pf_         = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
+    %     'ffe_mu_dd',mu_ffe,'ffe_mu_tr',0,'dfe_mu_dd',mu_dfe,'dfe_mu_tr',0.005,'sps',sps,'decide',0);
-    % mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
+    pf_         = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
-    % 
+    mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
-    % [vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Rx_synced, Symbols, Bits, ...
-    %     "precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", mapping_style);
-    % 
-    % mlse_results.metrics.print
-    % if our_signal
-    %     fprintf('Our Signal: %.1e \n',mlse_results.metrics.BER);
-    %     fprintf('Paper: %.1e \n \n',ber_in_paper);
-    % else
-    %     fprintf('Their Signal: %.1e \n',mlse_results.metrics.BER);
-    %     fprintf('Paper: %.1e \n \n',ber_in_paper);
-    % end
 
-    %% -------------------- ML-based MLSE (L=2) --------------------
+    [vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Rx_synced, Symbols, Bits, ...
-    ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ...
+        "precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", mapping_style);
-        "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",11,"sps",sps, ...
-        "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
 
-    [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
+    mlse_results.metrics.print
     if our_signal
-        fprintf('Our Signal: %.1e \n',ml_mlse_results.metrics.BER);
+        fprintf('Our Signal: %.1e \n',mlse_results.metrics.BER);
         fprintf('Paper: %.1e \n \n',ber_in_paper);
     else
-        fprintf('Their EQ: %.1e \n',ml_mlse_results.metrics.BER);
+        fprintf('Their Signal: %.1e \n',mlse_results.metrics.BER);
         fprintf('Paper: %.1e \n \n',ber_in_paper);
     end
+    
+    %% -------------------- ML-based MLSE (L=2) --------------------
+    % ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ...
+    %     "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",11,"sps",sps, ...
+    %     "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
+    % 
+    % [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
+    % if our_signal
+    %     fprintf('Our Signal: %.1e \n',ml_mlse_results.metrics.BER);
+    %     fprintf('Paper: %.1e \n \n',ber_in_paper);
+    % else
+    %     fprintf('Their EQ: %.1e \n',ml_mlse_results.metrics.BER);
+    %     fprintf('Paper: %.1e \n \n',ber_in_paper);
+    % end
 end

projects/FSO_transmission/Evaluation Scripts/plotscript_pam_2_optimal.m

@@ -0,0 +1,61 @@
+%%
+x = 225:10:285;
+averaging_over_signal_traces = 1;
+all_BER_plots = 0;
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(k) + '.mat');
+    BER_values = BER.BER_PAM_2;
+    idx_opt = BER.idx_opt;
+    BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
+    disp(idx_opt)
+
+    BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*7+1:k*7),:);
+
+    if averaging_over_signal_traces
+        for i = 1:size(BER_values,2)
+            BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
+        end
+    end
+
+    if all_BER_plots
+        figure;
+        hold on
+        for i = 1:size(BER_num_signal_sweep_matrix,1)
+            plot(BER_num_signal_sweep_matrix(i,:))
+        end
+        hold off
+    end
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+old_BER = [-1.5, -1.75, -2, -2.3, -2.6, -2.25, -1.95];
+old_BER = 10.^(old_BER);
+plot(x, old_BER, '-o','LineWidth',1.75)
+    
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
+       'Interpreter','latex', ...
+       'Location','southwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(221,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(221,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(231,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
+ylabel('BER', 'Interpreter','latex')
+% title('BER for PAM-2', 'Interpreter','latex')
+
+grid minor
+ylim([1e-4 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/Evaluation Scripts/plotscript_pam_4_optimal.m

@@ -0,0 +1,61 @@
+%%
+x = 225:10:285;
+averaging_over_signal_traces = 1;
+all_BER_plots = 0;
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(k) + '.mat');
+    BER_values = BER.BER_PAM_4;
+    idx_opt = BER.idx_opt;
+    BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
+    disp(idx_opt)
+
+    BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*7+1:k*7),:);
+
+    if averaging_over_signal_traces
+        for i = 1:size(BER_values,2)
+            BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
+        end
+    end
+    
+    if all_BER_plots
+        figure;
+        hold on
+        for i = 1:size(BER_num_signal_sweep_matrix,1)
+            plot(BER_num_signal_sweep_matrix(i,:))
+        end
+        hold off
+    end
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
+old_BER = 10.^(old_BER);
+plot(x, old_BER, '-o','LineWidth',1.75)
+    
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
+       'Interpreter','latex', ...
+       'Location','southwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(221,3.2e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(221,5.7e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(221,2.5e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
+ylabel('BER', 'Interpreter','latex')
+% title('BER for PAM-2', 'Interpreter','latex')
+
+grid minor
+ylim([3e-5 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/Evaluation Scripts/plotscript_pam_4_symbol_rate_sweep_optimal.m

@@ -0,0 +1,59 @@
+%%
+x = 4:1:8;
+averaging_over_signal_traces = 1;
+all_BER_plots = 0;
+for k = 1:4
+    BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(k) + '.mat');
+    BER_values = BER.BER_PAM_4;
+    idx_opt = BER.idx_opt;
+    BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
+    disp(idx_opt)
+
+    BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*5+1:k*5),:);
+
+    if averaging_over_signal_traces
+        for i = 1:size(BER_values,2)
+            BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
+        end
+    end
+    
+    if all_BER_plots
+        figure;
+        hold on
+        for i = 1:size(BER_num_signal_sweep_matrix,1)
+            plot(BER_num_signal_sweep_matrix(i,:))
+        end
+        hold off
+    end
+    
+    figure(202120)
+    plot(x, BER_values, '-o','LineWidth',1.75);
+    hold on
+end
+    
+h1 = yline(2e-2,  ':k', 'LineWidth',1.5);
+h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
+h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
+h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
+
+% Legende NUR für Kurven
+legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', ...
+       'Interpreter','latex', ...
+       'Location','southwest', 'FontSize', 14)
+
+% FEC Labels direkt im Plot
+text(3.2,2.3e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
+text(3.2,3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
+text(3.2,5.9e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
+text(3.2,2.7e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
+
+xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
+ylabel('BER', 'Interpreter','latex')
+% title('BER for PAM-2', 'Interpreter','latex')
+
+grid minor
+xlim([3 9])
+ylim([5e-7 5e-1])
+set(gca,'YScale','log')
+% beautifyBERplot
+hold off

projects/FSO_transmission/FSO_timing_recovery_minimal_example.m

@@ -236,8 +236,8 @@ for our_signal = 1
     % end
     
     %% -------------------- ML-based MLSE (L=2) --------------------
-    ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ...
+    ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
-        "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",80,"sps",sps, ...
+        "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",210,"sps",sps, ...
         "traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
 
     [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);