183 lines
6.6 KiB
Matlab
183 lines
6.6 KiB
Matlab
dsp_options.storage_path = 'Z:\2024\sioe_labor\';
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dsp_options.max_occurences = 1;
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database = DBHandler("dataBase", 'labor_highspeed', "type", 'mysql' );
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rates = [300e9];
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cols = cbrewer2('BuPu',25);
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cols = [cols(end-10:2:end,:)];
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cols = cbrewer2('Set1',6);
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fignum = 200;
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fig=figure(fignum);clf;
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for dbmode = 0:1%length(rates)
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if 0
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rcalpha = 0.05;
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fsym = rates/2;
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pulsef = 1;
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Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
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Pamsource = PAMsource(...
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"fsym",fsym,"M",4,"order",18,"useprbs",0,...
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"fs_out",fdac,...
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"applyclipping",0,"clipfactor",1.2,...
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"applypulseform",pulsef,"pulseformer",Pform,...
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"randkey",20,...
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"db_precode",dbmode,"db_encode",0,...
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"mrds_code",0,"mrds_blocklength",512);
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[Digi_sig,Symbols,Bits] = Pamsource.process();
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Digi_sig = Digi_sig.normalize("mode","rms");
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%%% 1) PLOT FULL RESPONSE SIGNAL
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Digi_sig.spectrum("displayname","Full Response","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",[0.2,0.2,0.2],"linestyle",'-','addDCoffset',0,'normalizeToDC',1);
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%%% 2) PLOT PREEMPH. TX SIGNAL
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if dbmode == 0
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maxamp = -37;
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precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
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precomp_path = "C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\precomp";
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precomp_fn = "lab_high_speed";
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Digi_sig_pre = precomp_est.precomp(Digi_sig,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
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Digi_sig_pre = Digi_sig_pre.resample("fs_out",fdac);
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Digi_sig_pre= Digi_sig_pre.normalize("mode","rms");
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Digi_sig_pre.spectrum("displayname","Strong Precomp","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",[0,0,0],"linestyle",'-.','addDCoffset',0,'normalizeToDC',1);
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end
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end
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% 1 - PAM 4 with preemphasis
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fp = QueryFilter();
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M = 4;
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fp.where('Runs', 'pam_level','EQUALS', M);
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fp.where('Runs', 'bitrate','EQUALS', rates);%360,390
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fp.where('Runs', 'fiber_length','EQUALS', 10);
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fp.where('Runs', 'wavelength','EQUALS', 1322.7); %1327.4
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fp.where('Runs', 'db_mode','EQUALS', dbmode);
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fp.where('Runs', 'rop_attenuation','EQUAL', 0);
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[dataTable,~] = database.queryDB(fp, database.getTableFieldNames('Runs'));
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dataTable = queryRunid(dataTable.run_id, database);
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fsym = dataTable.symbolrate;
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M = double(dataTable.pam_level);
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% Load and Sync signal data from DB
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[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncSignalDataFromDb(dataTable, dsp_options);
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% Preprocess signal
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Scpe_sig = preprocessSignal(Scpe_cell{1}, Symbols, fsym);
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Scpe_sig = Scpe_cell{1};
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%%% 3) PLOT DB Tgt. SIGNAL
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if 1
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DB_Symbols = Duobinary().encode(Symbols);
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DB_Symbols.spectrum("fignum",fignum+dbmode,"normalizeTo0dB",1,"displayname",'DB-Response','addDCoffset',0,'color',clr.Set1.blue,'normalizeToNyquist',0,'linestyle','--');
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end
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%%% 4) Plot RX Signal
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Scpe_sig.spectrum("fignum",fignum+dbmode,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',1,'color',[0,0,0],'normalizeToNyquist',0,'linestyle',':');
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Scpe_sig.eye(fsym,M,"fignum",47,"displayname",' Eye of AVG Signal');
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% xline(Symbols.fs/2.*1e-9,'Color',cols(r,:),'HandleVisibility','off');
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average_signals = 1;
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if average_signals
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Scpe_sig_avg = Scpe_sig;
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scope_mean = zeros(size(Scpe_cell{1}.signal));
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for n=1:numel(Scpe_cell)
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scope_mean = scope_mean + Scpe_cell{n}.signal;
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end
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scope_mean = scope_mean ./ n;
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Scpe_sig_avg.signal = scope_mean;
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Scpe_sig_avg.spectrum("displayname","Scope PSD","fignum",20,"normalizeTo0dB",1);
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Scpe_sig_avg.plot("displayname","Scope raw signal","fignum",27,"clear",1);
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Scpe_sig_avg.eye(fsym,M,"fignum",48,"displayname",' Eye of AVG Signal');
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end
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fig = figure(fignum+dbmode);
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if dbmode == 0
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ylim([-22,12]);
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else
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ylim([-22,2]);
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end
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xlim([0,105]);
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xticks(-100:20:100);
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yticks(-20:10:10);
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beautifyBERplot("logscale",0,"setmarkers",0)
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pos = [100.3333 991.6667 358.0000 192.6667];
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set(fig, 'Position', pos);
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%%%%%%%%%%%%
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drawnow;
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% Do EQ and find alpha's
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len_tr = 4096*2;
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ffe_order = [50, 5, 5];
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dfe_order = [0, 0, 0];
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pf_ncoeffs = 1;
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mu_ffe = [0.0001, 0.0008, 0.001];
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mu_dfe = 0.0004;
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mu_dc = 0.005;
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%%% FULL RESP TARGET
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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",0);
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pf_1 = Postfilter("ncoeff",1,"useBurg",1);
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[eq_signal_sd, eq_noise] = eq_.process(Scpe_sig, Symbols);
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% eq_noise.signal = eq_noise.signal - mean(eq_noise.signal);
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% eq_noise = eq_noise.normalize("mode","rms");
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[mlse_sig_sd,whitened_noise] = pf_1.process(eq_signal_sd, eq_noise);
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fig = figure(fignum+dbmode+10); hold on
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[h, w] = freqz(1, pf_1.coefficients, length(eq_noise), "whole", eq_noise.fs);
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h = h / max(abs(h)); % Normalize the filter response
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w_ = (w - eq_noise.fs / 2);
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%%% DB TARGET
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db_ref_sequence = Duobinary().encode(Symbols);
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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",0);
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[eq_signal, db_noise] = eq_.process(Scpe_sig,db_ref_sequence);
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% db_noise.signal = db_noise.signal - mean(db_noise.signal);
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% db_noise = db_noise.normalize("mode","rms");
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%%% 1-3) Plot EQ Noise EEN
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figure(fignum+dbmode+10)
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eq_noise.spectrum("displayname", 'Noise', "fignum", fignum+dbmode+10, "normalizeTo0dB", 0,"color",clr.Set1.green,"normalizeToDC",0,"addDCoffset",0);
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if dbmode == 1
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offset = 27.7;
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else
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offset = 29.8;
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end
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plot(w_ * 1e-9, 20 * log10(fftshift(abs(h)))-offset, 'DisplayName', ['Burg Coeffs: ', num2str(round(pf_1.coefficients, 2)), ' '], 'LineWidth', 1,'Color',clr.Set1.green,'LineStyle','--');
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db_noise.spectrum("displayname", 'DBt. Noise', "fignum", fignum+dbmode+10, "normalizeTo0dB", 0,"color",clr.Set1.blue,"normalizeToDC",0,"addDCoffset",0);
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ylim([-54,-25]);
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xlim([0,105]);
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xticks(0:20:110);
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yticks(-50:10:10);
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beautifyBERplot("logscale",0,"setmarkers",0)
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pos = [100.3333 991.6667 358.0000 192.6667];
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set(fig, 'Position', pos);
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end
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% === FINAL FIGURE SIZE ===
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