3676d92b30
+ duobinary_target now supports memoryless decoding (FFE targets DB response without MLSE) + PAMmapper.quantize now supports custom constellations for quantization + Added a new folder 'Documentations' for pdfs, slides, etc. + Added new FSO evaluation scripts in projects/FSO transmission/Evaluation Scripts + Added ffe_db (rudimentary module, not important anymore)
180 lines
8.1 KiB
Matlab
180 lines
8.1 KiB
Matlab
function BER_value = first_analysis_fso(current, power, baudrate, baudrate_e, rolloff, ...
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num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal)
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%% Close Remaining Figures
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close all
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%% Load Data
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base = "C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\Sweep Data\";
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mode = 0; %0 oder 1
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tx_data_path = fullfile(base, string(baudrate) + "G_PAM" + string(M) + "\tx_info\tx_info_PAM" + string(M) + "_" + string(baudrate) + "Gbd" + string(rolloff) + "RRC.mat");
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filename = fullfile(base, string(baudrate) + "G_PAM" + string(M) + "\M=" + string(M) + "_Rs=" + baudrate_e + "_Fs=8e10_I=" + string(current) + "mA_RoP=" + string(power) + "mW_L=31m_PS=RRC_rolloff=" + string(rolloff) + "_Mode=Rise.mat");
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if mode == 1
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[f, p] = uigetfile(fullfile(base, "**/*.mat"));
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if f~=0
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filename = fullfile(p,f);
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end
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end
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tx_data = load(tx_data_path);
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datas = load(filename);
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%%
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str = filename;
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M_ = str2double(regexp(str, 'M=([^_]+)', 'tokens', 'once'));
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assert(M==M_);
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fsym = str2double(regexp(str, 'Rs=([^_]+)', 'tokens', 'once'));
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fs = str2double(regexp(str, 'Fs=([^_]+)', 'tokens', 'once'));
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I = sscanf(char(regexp(str, 'I=([^_]+)', 'tokens', 'once')), '%f');
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rop = sscanf(char(regexp(str, 'RoP=([^_]+)', 'tokens', 'once')), '%f');
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L = sscanf(char(regexp(str, 'L=([^_]+)', 'tokens', 'once')), '%f');
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pulseshape = string( regexp(str, 'PS=([^_]+)', 'tokens', 'once'));
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rolloff = str2double(regexp(str, 'rolloff=([^_]+)', 'tokens', 'once'));
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mode = string( regexp(str, 'Mode=([^\.]+)', 'tokens', 'once'));
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%% Generate Tx Data
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Bits = Informationsignal(tx_data.tx_data,"fs",fsym);
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Symbols = Informationsignal(real(tx_data.tx_PAM_sym),"fs",fsym);
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mapping_style = M==4; % Pam2 is like move-it; PAM-4 is different, same mapping like ETH peopled used in Zurich... hence the "eth_style" argument here and there
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PM = PAMmapper(M,0,"eth_style",mapping_style); % one should rename "eth style" as this is simply a different mapping scheme
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Symbols_ = PM.map(Bits) .* PM.scaling;
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assert(isequal(Symbols.signal,Symbols_.signal));
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Bits_ = PM.demap(Symbols);
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[bits,errors,ber,errorIndice] = calc_ber(Bits_.signal,Bits.signal);
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assert(ber == 0);
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%% For comparison, apply pulsef on Tx Symbols
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Pform = Pulseformer("fsym",fsym,"fdac",fs,"pulse","rrc","pulselength",16,"alpha",rolloff);
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Digi_sig_compare = Pform.process(Symbols);
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MF = Pulseformer("fsym",fsym,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rolloff);
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Rx_sig_compare = MF.process(Digi_sig_compare);
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%% Matched Filter
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traceData = datas.tr.lastData(2).trace.ch3;
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%FYI: Voltage=(RawData−YReference)×YIncrement+YOrigin
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scoperead_volts = (traceData.RawData - traceData.YReference) * traceData.YIncrement + traceData.YOrigin;
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demystified = isequal(traceData.YData,scoperead_volts);
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assert(demystified);
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Scope_sig = Electricalsignal(traceData.YData,"fs",fs);
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Scope_sig.plot("displayname",'raw','fignum',100);
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Scope_sig.spectrum("displayname",'raw','fignum',101)
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Kov = 14;
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Scope_sig = Scope_sig.resample('fs_in', fs, 'fs_out', Kov*fsym);
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% Apply Matched Filter
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Matched_Filter = Pulseformer("fsym",fsym,"fdac",Kov*fsym,"pulse","rrc","pulselength",16,"alpha",rolloff,"matched",1);
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Rx_matched = Matched_Filter.process(Scope_sig);
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Rx_matched.spectrum("displayname",'Signal after matched filter','fignum',1);
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%% Timing Synchronization
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[~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
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Rx_matched_1 = Rx_synced_cell{num_signal};
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%% Timing Recovery
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Time_Rec = 1;
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if Time_Rec
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Rx_Time_Rec = MaxVar_Timing_Recovery('mode',0,'fsym',fsym,'fadc',Kov*fsym,'num_tau',Kov*128,'sps',Kov,'comp_signal',0,'comp_mode',0).process(Rx_matched_1);
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sps = 1;
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else
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sps = Kov;
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end
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Rx_Time_Rec.fs = fsym;
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Rx_Time_Rec = Rx_Time_Rec.normalize('mode','rms');
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%% DSP Parameters
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Rx_synced = Rx_Time_Rec;
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len_tr = trlength;
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mu_ffe1 = 0.0001;
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mu_ffe2 = 0.0008;
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mu_ffe3 = 0.001;
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mu_dc = 0.004;
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mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
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mu_dfe = 0.0004;
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duob_mode = db_mode.no_db;
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if M == 2
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ber_in_paper = 10^(-2.6); %fig 3a) 4 Gb/s MWIR FSO Transmission using Directly Modulated QCL and an Uncooled UTC-PD at Room-Temperature
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elseif M == 4
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ber_in_paper = 10^(-2.5);
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end
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%% EQ Methods
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if eq_method == 1
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% -------------------- FFE --------------------
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% requires some more digging what is going on :-)
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eq_ffe = EQ("Ne",[500, 0, 0],"Nb",[0, 0, 0], ...
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"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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ffe_results = ffe(eq_ffe,M,Rx_synced,Symbols,Bits, ...
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"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
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"eth_style_symbol_mapping",mapping_style);
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% ffe_results.metrics.print
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fprintf('My EQ: %.1e \n',ffe_results.metrics.BER);
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fprintf('Paper: %.1e \n \n',ber_in_paper);
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BER_value = ffe_results.metrics.BER;
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elseif eq_method == 2
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% -------------------- VNLE + MLSE --------------------
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pf_ncoeffs = num_pf_coeff;
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eq_v = EQ("Ne",taps_ffe,"Nb",taps_dfe, ...
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"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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"FFEmu",0,"plotfinal",0,"ideal_dfe",0,'weighted_DFE',0,'weighted_DFE_d_min',0.5, ...
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'weighted_DFE_mode','I2','weighted_DFE_I_mode',0,'PDFE_coefficient',0.01);
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
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[vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Rx_synced, Symbols, Bits, ...
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"precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", mapping_style);
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mlse_results.metrics.print
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fprintf('My EQ: %.1e \n',mlse_results.metrics.BER);
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fprintf('Paper: %.1e \n \n',ber_in_paper);
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BER_value = mlse_results.metrics.BER;
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elseif eq_method == 3
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% -------------------- DB target --------------------
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mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
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eq_ = EQ("Ne",taps_ffe,"Nb",taps_dfe,"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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dbt_results = duobinary_target(eq_,mlse_db_, M, Rx_synced, Symbols, Bits, ...
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"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [],"eth_style_symbol_mapping",mapping_style,"decoding_mode","sequencedetection");
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dbt_results.metrics.print("description",'Duobinary');
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fprintf('My EQ: %.1e \n',dbt_results.metrics.BER);
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fprintf('Paper: %.1e \n \n',ber_in_paper);
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BER_value = dbt_results.metrics.BER;
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elseif eq_method == 4
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% -------------------- ML-based MLSE (L=2) --------------------
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ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
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"len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",filter_length,"sps",1, ...
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"traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
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[ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
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fprintf('ML-based MLSE:\n');
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fprintf('My EQ: %.1e \n',ml_mlse_results.metrics.BER);
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fprintf('Paper: %.1e \n \n',ber_in_paper);
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BER_value = ml_mlse_results.metrics.BER;
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end
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end |