% Minimal IMDD model for investigating FFE noise enhancement. % Parameters mirror the current IMDD_base_system/imdd_it.m, % IMDD_base_system/imdd_model.m, and the FFE branch in dsp_scope_signal.m. clearvars; close all; %% Sweep parameters from imdd_it.m fsym_values = (152:16:200).*1e9; precomp = 0; laser_wavelength = 1310; M = 4; link_length = 2; channel_alpha = 0.5; duob_mode = db_mode.db_precoded; decoding_mode = db_decoder.sequencedetection; channel_mode = channel_model.physical; channel_snr_dB = 20; rop_values = -8:2:4; %% Inner model parameters from imdd_model.m bitrate = []; apply_pulsef = 0; fdac = 256e9; fadc = 256e9; random_key = 1; rcalpha = 0.05; kover = 16; vbias_rel = 0.5; u_pi = 3; vbias = -vbias_rel*u_pi; laser_linewidth = 0; eml_alpha = 0; len_tr = 4096*2; pf_ncoeffs = 1; mu_dc = 0.005; nRates = numel(fsym_values); nRops = numel(rop_values); eq_names = ["FFE","VNLE"]; nEqs = numel(eq_names); emptyResult = struct("fsym",[],"ROP",[],"equalizer",[],"BER",[],"SNR",[],"numBitErr",[], ... "eq_noise",[],"eq_signal_sd",[],"eq",[],"Rx_sig",[],"Tx_sig",[],"Tx_symbols",[]); results = repmat(emptyResult,nRates,nRops,nEqs); cols = flip(cbrewer2('RdYlBu',nRates+4)); midIdx = floor(size(cols,1)/2) + (-1:2); cols(midIdx,:) = []; for i = 1:numel(fsym_values) fsym = fsym_values(i); fprintf("Running %.0f GBd (%d/%d)\n", fsym*1e-9, i, numel(fsym_values)); if isempty(bitrate) bitrateCurrent = fsym * log2(M); end Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha); [Digi_sig, Symbols, ~] = 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(); rateResults = repmat(emptyResult,nRops,nEqs); Tx_sig = Digi_sig; El_sig = M8199B("kover",kover).process(Digi_sig); tx_bwl = 85e9; El_sig = Filter("filtdegree",4,"f_cutoff",tx_bwl,"fs",fdac*kover, ... "filterType",filtertypes.bessel_inp,"active",true).process(El_sig); El_sig = El_sig.normalize("mode","oneone"); scaling = 0.7*(u_pi/2-abs(vbias-u_pi/2)); El_sig = El_sig .* scaling; 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",eml_alpha).process(El_sig); 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); parfor j = 1:nRops rop = rop_values(j); fprintf(" ROP %.1f dBm (%d/%d)\n", rop, j, nRops); Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power", ... "amplification_db",rop).process(Opt_sig); Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08, ... "responsivity",0.6,"temperature",20,"nep",1.8e-11).process(Rx_sig); rx_bwl = 90e9; Rx_sig = Filter("filtdegree",4,"f_cutoff",rx_bwl,"fs",fdac*kover, ... "filterType",filtertypes.butterworth,"active",true).process(Rx_sig); Lp_scpe = Filter("filtdegree",4,"f_cutoff",110e9,"fs",fadc, ... "filterType",filtertypes.butterworth,"active",true); Rx_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); txPulseformer = []; if apply_pulsef txPulseformer = Pform; end Scpe_sig = preprocessSignal(Rx_sig, Symbols, fsym, ... "mode","auto", ... "tx_pulseformer",txPulseformer, ... "debug_plots",0); Scpe_sig.signal = Scpe_sig.signal(1:2*Symbols.length); Scpe_sig.signal = real(Scpe_sig.signal); for k = 1:nEqs switch eq_names(k) case "FFE" eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr, ... "mu_dd",1e-1,"mu_tr",0.4,"order",50, ... "sps",2,"decide",0,"optmize_mus",1,"dd_mode",1, ... "adaption_technique","nlms","mu_dc",1.021e-05); case "VNLE" eq_ = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr, ... "mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0, ... "order",[25,2,2],"sps",2,"decide",0, ... "optmize_mus",1,"mu_dc",0.1); end [eq_signal_sd, eq_noise] = eq_.process(Scpe_sig, Symbols); eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd); rx_bits = PAMmapper(M,0).demap(eq_signal_hd); tx_bits_demapped = PAMmapper(M,0).demap(Symbols); [~, errors, ber] = calc_ber(rx_bits.signal, tx_bits_demapped.signal, ... "skip_front",10,"skip_end",10); localResult = emptyResult; localResult.fsym = fsym; localResult.ROP = rop; localResult.equalizer = eq_names(k); localResult.BER = ber; localResult.SNR = snr(eq_signal_sd.signal, eq_noise.signal); localResult.numBitErr = errors; localResult.eq_noise = eq_noise; localResult.eq_signal_sd = eq_signal_sd; localResult.eq = eq_; localResult.Rx_sig = Rx_sig; localResult.Tx_sig = Tx_sig; localResult.Tx_symbols = Symbols; rateResults(j,k) = localResult; end end results(i,:,:) = reshape(rateResults,1,nRops,nEqs); end %% Plot section close all berGrid = reshape([results.BER],nRates,nRops,nEqs); figure(400); clf; for k = 1:nEqs subplot(1,nEqs,k); plot(fsym_values.*1e-9, berGrid(:,:,k), "LineWidth",0.8, ... "LineStyle","-","Marker",".","MarkerSize",15); set(gca,"YScale","log"); grid on; grid minor; xlabel("Symbol rate (GBd)"); ylabel("BER"); title(eq_names(k) + " BER vs. Symbol Rate"); legend(compose("ROP %.1f dBm",rop_values),"Location","best"); end %% figure(500); clf; for k = 1:nEqs subplot(1,nEqs,k); plot(rop_values, berGrid(:,:,k).', "LineWidth",0.8, ... "LineStyle","-","Marker",".","MarkerSize",15); set(gca,"YScale","log"); grid on; grid minor; xlabel("ROP"); ylabel("BER"); title(eq_names(k) + " BER vs. ROP"); legend(compose("%.0f GBd",fsym_values.*1e-9),"Location","best"); end %% plotResults = reshape(results(:,end,:),nRates,nEqs); for k = 1:nEqs for i = 1:nRates fsym = plotResults(i,k).fsym; eq_noise = plotResults(i,k).eq_noise; eq_signal_sd = plotResults(i,k).eq_signal_sd; Rx_sig = plotResults(i,k).Rx_sig; Tx_sig = plotResults(i,k).Tx_sig; Tx_symbols = plotResults(i,k).Tx_symbols; displayName = sprintf('%s, %d GBd, ROP %.1f dBm',plotResults(i,k).equalizer,fsym.*1e-9,plotResults(i,k).ROP); showEQNoisePSD(eq_noise, "fignum", 1, "displayname", displayName,"color",cols(i,:)); xlim([0, 120]) % mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/ffe_noise_enhancement/noise_psd.tex") Tx_sig.normalize("mode","rms").spectrum("displayname",displayName,'fignum',2,'normalizeTo0dB',0,"color",cols(i,:),"linestyle",'-','HandleVisibility','on'); xlim([0, 120]) % mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/ffe_noise_enhancement/tx_signals.tex") Rx_sig.normalize("mode","rms").spectrum("displayname",displayName,'fignum',3,'normalizeTo0dB',0,"color",cols(i,:)); xlim([0, 120]) % mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/ffe_noise_enhancement/rx_signals.tex") showEQNoiseSNR(eq_signal_sd, eq_noise,"displayname",displayName,"color",cols(i,:),"fignum",4); xlim([0, 120]) % mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/ffe_noise_enhancement/snr_after_ffe.tex") % showEQfilter(plotResults(i,k).eq.e, eq_signal_sd.fs.*2,"displayname",displayName,'fignum',5,"color",cols(i,:)); % xlim([0, 120]); fprintf('%s BER %.2e \n',plotResults(i,k).equalizer,plotResults(i,k).BER) if i == 1 || i == nRates-1 || i == nRates show2Dconstellation(PAMmapper(M,0).get_scaling.*eq_signal_sd.signal(1:end), PAMmapper(M,0).get_scaling.*Tx_symbols.signal(1:end), ... "displayname",displayName, ... "fignum",5+(k-1)*nRates+i, ... "clear",i == 1 && k == 1,"rasterize", false); mat2tikz_improved(sprintf("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/ffe_noise_enhancement/noise_correlation_%s.tex",displayName),"cleanfigure",true); eq_signal_sd.eye(fsym,M,"fignum",8+(k-1)*nRates+i,"mode",1); end end end %%