new minimal example

new project: FSO stuff

Classes/00_signals/Electricalsignal.m

@@ -108,9 +108,6 @@ classdef Electricalsignal < Signal
             obj.signal = obj.signal*scling;
 
         end
-
-
-
     end
 end
 

Classes/00_signals/Opticalsignal.m

@@ -70,8 +70,7 @@ classdef Opticalsignal < Signal
             s = mean( abs(obj.signal-mean(obj.signal)).^2 );
             cspr = 10*log10(c / s);
 
-            
+           
-
         end
 
 

Classes/00_signals/Signal.m

@@ -98,7 +98,6 @@ classdef Signal
 
         end
 
-
         %% CONVERT TO Opticalsignal
         function o_sig = Opticalsignal(obj, options)
 
@@ -273,7 +272,6 @@ classdef Signal
             SignalCopy  = [];
             ModifierName = class(CallingModifier);
 
-
             cell = {SignalType , TimeStamp , Length , SignalPower(1) , Nase, SignalCopy, ModifierName, ModifierCopy, Description};
 
             obj.logbook = [obj.logbook; cell];
@@ -363,8 +361,7 @@ classdef Signal
                 options.fft_length = 2^(nextpow2(length(obj.signal))-9);
             end
 
-            
+           
-
             if options.normalizeToNyquist == 0
                 [p_lin,f_Hz] = pwelch(obj.signal, hanning(options.fft_length), ...
                     options.fft_length/2, options.fft_length, ...
@@ -488,7 +485,6 @@ classdef Signal
         end
 
 
-
         function move_it_spectrum(obj,options)
             arguments
                 obj
@@ -630,7 +626,6 @@ classdef Signal
 
                 case power_notation.W
                     %pow = pow % Watt
-
             end
 
         end
@@ -668,7 +663,7 @@ classdef Signal
 
         %% PAPR of signal
         function papr_db = papr_db(obj)
-            %PAPR The peak-to-average power ratio (PAPR) is the peak amplitude squared (giving the peak power)
+            % PAPR The peak-to-average power ratio (PAPR) is the peak amplitude squared (giving the peak power)
             % divided by the RMS value squared (giving the average power).[1] It is the square of the crest factor.
             % papr = max(abs(timesignal))^2 / rms(timesignal)^2; ODER papr = peak2rms(sig)^2;
 
@@ -722,7 +717,7 @@ classdef Signal
 
         end
 
-        %%
+        %%  
         function [obj,S,inverted,sequenceFound,sequenceStarts] = tsynch(obj,options)
             % time sync and cut
             arguments
@@ -732,14 +727,11 @@ classdef Signal
                 options.debug_plots = 0;
             end
 
-
-
             S = {};
             inverted = -1;
             sequenceFound = 0;
             sequenceStarts = [];
 
-
             %normalize the signal
             a = obj.normalize("mode","oneone").signal;
 
@@ -777,8 +769,6 @@ classdef Signal
                 findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend')
             end
 
-
-
             shifts = lags(pkpos);
             sequenceStarts = shifts;
             shifts = shifts(shifts>=0);
@@ -831,7 +821,6 @@ classdef Signal
 
         end
 
-
         %%
         function obj = filter(obj,a,b)
 
@@ -921,6 +910,7 @@ classdef Signal
 
 
         end
+        
         %%
         function eye(obj,fsym,M,options)
 
@@ -981,8 +971,8 @@ classdef Signal
                 maxA = max(sig(100:end-100))*1.3;
                 minA = min(sig(100:end-100))*1.3;
 
-                maxA = 0.12;
+                % maxA = 0.12;
-                minA = -0.08;
+                % minA = -0.08;
 
                 difference= maxA-minA;
 

Functions/Metrics/air_garcia_implementation.m

@@ -11,7 +11,6 @@ if nargin == 4
     M_training = [];
 end
 
-
 % if input is complex, separate into real and imaginary parts
 if any(imag(x(:))~=0) || any(imag(r(:))~=0)
     x = [real(x); imag(x)];

projects/FSO_transmission/first_analysis.m

@@ -0,0 +1,12 @@
+
+datas = load("C:\Users\Silas\Downloads\FSO_FP_QCL_60umUTC\FSO_FP_QCL_60umUTC\6G_PAM4\M=4_Rs=6e9_Fs=8e10_I=225mA_RoP=28.02mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
+
+fsym = 6e9;
+fs = 80e9;
+
+rawsignal = datas.tr.lastData(1).trace.ch3.RawData;
+
+Scope_sig = Electricalsignal(rawsignal,"fs",fs);
+
+Scope_sig.plot("displayname",'raw','fignum',100);
+

projects/IMDD_base_system/imdd_it.m

@@ -1,6 +1,7 @@
 
 
 if 1
+    
     uloops          = struct;
     uloops.precomp      = [1];
     uloops.bitrate      = [300].*1e9; %[300,330,360,390,420,450,480] [224,336,360,390,420,448] for MPI
@@ -8,12 +9,12 @@ if 1
     uloops.laser_wavelength = [1293];
     uloops.M            = [4];
     uloops.link_length  = [0:2:10]; % 1,2,3,5,6,8,10
-    uloops.alpha = [0.5,-0.5,0];
+    uloops.alpha = [0];
 
     wh = DataStorage(uloops);
     wh.addStorage("ber");
 
-    wh = submit_handle(@imdd_model,wh,"parallel",1);
+    wh = submit_handle(@imdd_model,wh,"parallel",0);
 
 end
 
@@ -34,6 +35,8 @@ beautifyBERplot()
 ylabel('BER');
 
 
+
+
 % 
 % wh_ana = wh_master;
 % 

projects/IMDD_base_system/imdd_model.m

@@ -92,9 +92,13 @@ if 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;
 
-Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
+Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
 
 [Digi_sig,Symbols,Tx_bits] = PAMsource(...
     "fsym",fsym,"M",M,"order",18,"useprbs",0,...

projects/IMDD_base_system/minimal_example.m

@@ -0,0 +1,156 @@
+% minimal example IM/DD
+
+M               = 4;
+fsym            = 180e9;
+
+apply_pulsef    = 1;
+fdac            = 256e9;
+fadc            = 256e9;
+random_key      = 1;
+
+rcalpha         = 0.05;
+kover           = 16;
+
+duob_mode = db_mode.no_db;
+
+vbias_rel       = 0.5;
+u_pi            = 3;
+vbias           = -vbias_rel*u_pi;
+
+laser_wavelength    = 1293;
+laser_linewidth     = 0;
+tx_bw_nyquist   = 0.8;
+
+% Channel
+link_length     = 1;
+
+% RX
+rop = -8;
+rx_bw_nyquist = 0.8;
+
+vnle_order1 = 50;
+vnle_order2 = 7;
+vnle_order3 = 7;
+
+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;
+
+
+Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
+
+[Digi_sig,Symbols,Tx_bits] = PAMsource(...
+    "fsym",fsym,"M",M,"order",18,"useprbs",0,...
+    "fs_out",fdac,...
+    "applyclipping",0,"clipfactor",1.5,...
+    "applypulseform",apply_pulsef,"pulseformer",Pform,...
+    "randkey",random_key,...
+    'duobinary_mode',duob_mode,...
+    "mrds_code",0,"mrds_blocklength",512).process();
+
+%%%%% AWG
+El_sig = M8199A("kover",kover).process(Digi_sig);
+% El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
+El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',0);
+% El_sig = El_sig.setPower(0,"dBm");
+
+%%%%% Electrical Driver Amplifier %%%%%%
+% El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
+El_sig = El_sig.normalize("mode","oneone");
+scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2));
+El_sig = El_sig .* scaling;
+
+%%%%% MODULATE E/O CONVERSION %%%%%%
+[Opt_sig] = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs,"lambda",laser_wavelength,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",random_key+1,"alpha",alpha).process(El_sig);
+
+Opt_sig.spectrum("displayname",'Opt Spectrum','fignum',10,'normalizeTo0dB',1);
+
+% Opt_sig.eye(fsym,M,"displayname",'eye adter modulator','fignum',2026);
+
+Opt_sig    = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.07).process(Opt_sig);
+
+%%%%%% ROP %%%%%%
+Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
+
+%%%%%% PD Square Law %%%%%%
+Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11).process(Rx_sig);
+
+%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
+rx_bwl = 80e9;
+Rx_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
+
+% %%%%%% Low-pass Scope %%%%%%
+Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
+
+%%%%%% Scope %%%%%%
+Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
+    "delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
+    "samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
+    "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(Rx_sig);
+
+%%%%%% Sample to 2x fsym %%%%%%
+Scpe_sig =  Scpe_sig.resample("fs_out",2*fsym);
+Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
+
+%%%%%% Sync Rx signal with reference %%%%%%
+[Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
+Scpe_sig.spectrum("displayname",'Opt Spectrum','fignum',11,'normalizeTo0dB',1);
+
+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);
+
+% -------------------- FFE --------------------
+ffe_order   = [50, 0, 0];
+eq_ffe      = EQ("Ne",ffe_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);
+
+output.ffe_results = ffe(eq_ffe,M,Scpe_sig,Symbols,Tx_bits, ...
+    "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
+    "eth_style_symbol_mapping",0);
+
+output.ffe_results.metrics.print
+
+% -------------------- VNLE + MLSE --------------------
+pf_ncoeffs  = 1;
+ffe_order3  = [50, 5, 5];
+eq_v        = EQ("Ne",ffe_order3,"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("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
+
+[output.vnle_results, output.mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
+    "precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [], "eth_style_symbol_mapping", 0);
+
+
+% -------------------- DB target --------------------
+mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
+ffe_order = [50, 5, 5];
+eq_       = EQ("Ne",ffe_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);
+output.dbt_results = duobinary_target(eq_,mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
+    "precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", []);
+
+output.dbt_results.metrics.print("description",'Duobinary');
+
+
+