230 lines
8.2 KiB
Matlab
230 lines
8.2 KiB
Matlab
%%% Run parameters
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% TX
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M = 4;
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m = floor(log2(M)*10)/10;
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fsym = 224e9;
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apply_pulsef = 1;
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fdac = 256e9;
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fadc = 256e9;
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random_key = 2;
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rcalpha = 0.05;
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kover = 8;
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vbias_rel = 0.5;
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u_pi = 3.2;
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vbias = -vbias_rel*u_pi;
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laser_wavelength = 1310;
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laser_linewidth = 1e6;
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% Channel
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link_length = 0;
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vnle_order1 = 50;
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vnle_order2 = 0;
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vnle_order3 = 0;
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vnle_order=[vnle_order1,vnle_order2,vnle_order3];
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dfe_order = [0 0 0];
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alpha = 0;
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len_tr = 4096*2;
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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 = 0.005;
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% mu_dc = 0;
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mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
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mu_dfe = 0.0004;
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dfe_ = sum(dfe_order)>0;
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doub_mode = db_mode.no_db;
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cols = linspecer(6);
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rop = [-8];
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bwl = [0.5:0.1:1.5];
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fsym = [208:16:256].*1e9;
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nonlin_mod = [0.5:0.01:0.75];
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fsym = ones(size(nonlin_mod)).*fsym(1);
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ffe_results = {};
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mlse_results_lin= {};
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vnle_results= {};
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mlse_results_nonlin= {};
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mlse_results_nonlin_states= {};
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g_eye = GifWriter('Name','eye','Parallel',true);
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g_mod = GifWriter('Name','modulator','Parallel',true);
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for r = 1:length(nonlin_mod)
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Pform = Pulseformer("fsym",fsym(r),"fdac",4*fsym(r),"pulse","rc","pulselength",16,"alpha",rcalpha);
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db_precode = 0;
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db_encode = 0;
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duob_mode = db_mode.no_db;
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apply_pulsef = 1;
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[Digi_sig,Symbols,Tx_bits] = PAMsource(...
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"fsym",fsym(r),"M",M,"order",19,"useprbs",0,...
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"fs_out",fdac,...
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"applyclipping",0,"clipfactor",1.5,...
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"applypulseform",apply_pulsef,"pulseformer",Pform,...
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"randkey",random_key,...
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"db_precode",db_precode,"db_encode",db_encode,...
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"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
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% El_sig = AWG("fdac",fdac,"f_cutoff",fsym(r),"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",0).process(Digi_sig);
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El_sig = M8199B("kover",kover).process(Digi_sig);
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% AWG("fdac",fdac,"f_cutoff",fsym(r),"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",0).process(Digi_sig);
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%%%%% Low-pass el. components %%%%%%
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% tx_bwl = 100e9;
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% El_sig = Filter('filtdegree',3,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
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%%%%% Electrical Driver Amplifier %%%%%%
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El_sig = El_sig.normalize("mode","oneone");
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% El_sig = El_sig.setPower(1,"dBm");
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% figure;histogram(El_sig.signal);
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%%%%% MODULATE E/O CONVERSION %%%%%
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u_pi = 3.2;
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vbias = -u_pi*nonlin_mod(r);
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[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).process(El_sig);
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if 1
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figure(15);
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hold on
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scatter(El_sig.signal(1:100000)+vbias,(abs(Opt_sig.signal(1:100000)).^2)*1e3,0.1,'.','DisplayName','Modulator TF')
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xlabel('Input in V')
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ylabel('abs(Eopt)2 in mW','Interpreter','latex')
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ylim([0 2]);
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xlim([-3.2 0]);
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g_mod.addFrame(15, r);
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Opt_sig.eye(fsym(r), M, "fignum", 103837);
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g_eye.addFrame(103837, r);
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end
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%%%%%% Fiber %%%%%%
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Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length/1000,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.07).process(Opt_sig);
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%%%%%% ROP %%%%%%
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Opt_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
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%%%%%% PD Square Law %%%%%%
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PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",random_key).process(Opt_sig);
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%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
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rx_bwl = 70e9;
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PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig);
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% %%%%%% Low-pass Scope %%%%%%
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Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
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%%%%%% Scope %%%%%%
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Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
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"delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
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"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
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"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(PD_sig);
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Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym(r));
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% Scpe_sig_resampled.signal = Scpe_sig_resampled.signal(1:2*length(Symbols));
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[~, Scpe_cell, ~, found_sync] = Scpe_sig_2sps.tsynch("reference", Symbols, "fs_ref", fsym(r), "debug_plots", 0);
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Rx_sig = Scpe_cell{1};
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Rx_sig = Rx_sig.normalize("mode","rms");
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if 1
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%% FFE
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% ffe_order = [50, 0, 0];
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% 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);
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%
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% ffe_results = ffe(eq_ffe,M,Rx_sig,Symbols,Tx_bits,...
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% "precode_mode",duob_mode,...
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% 'showAnalysis',0,...
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% "postFFE",[],...
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% "eth_style_symbol_mapping",0);
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%
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% ffe_results.metrics.print;
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% ffe_results.config.equalizer_structure = "ffe";
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%
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%% MLSE linear
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pf_ncoeffs = 1;
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ffe_order = [50, 0, 0];
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eq_ = 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",1);
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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).levels,'scale_mode',2,'trellis_exclusion',0,'trellis_state_mode',2,'debug',1);
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[ffe_results{r}, mlse_results_lin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode,...
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'showAnalysis', 0, ...
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"postFFE", [],...
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"eth_style_symbol_mapping", 0);
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mlse_results_lin{r}.metrics.print;
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ffe_results{r}.metrics.print;
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%% MLSE nonlinear pre
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pf_ncoeffs = 1;
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ffe_order = [50, 1, 0];
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eq_ = 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",1);
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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).levels,'scale_mode',2,'trellis_exclusion',0,'trellis_state_mode',2);
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[vnle_results{r}, mlse_results_nonlin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode,...
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'showAnalysis', 0, ...
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"postFFE", [],...
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"eth_style_symbol_mapping", 0);
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mlse_results_nonlin{r}.metrics.print;
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vnle_results{r}.metrics.print;
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%% nonlinear states MLSE linear pre
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pf_ncoeffs = 1;
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ffe_order = [50, 0, 0];
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eq_ = 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",1);
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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).levels,'scale_mode',2,'trellis_exclusion',0,'trellis_state_mode',3);
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[~, mlse_results_nonlin_states{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode,...
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'showAnalysis', 0, ...
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"postFFE", [],...
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"eth_style_symbol_mapping", 0);
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mlse_results_nonlin_states{r}.metrics.print;
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end
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end
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g_mod.compile(15);
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g_eye.compile(103837);
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%%
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figure();hold on;
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plot(nonlin_mod,cellfun(@(x) x.metrics.BER, ffe_results),'DisplayName','FFE')
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plot(nonlin_mod,cellfun(@(x) x.metrics.BER, vnle_results),'DisplayName','VNLE')
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plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_lin),'DisplayName','FFE+MLSE')
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plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_nonlin_states),'DisplayName','FFE+nonlin. states MLSE')
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plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_nonlin),'DisplayName','VNLE+MLSE')
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xlabel('Nonlinear Driving');
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ylabel('BER')
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set(gca,'YScale','log');
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legend;
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ylim([1e-4 1e-1]);
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beautifyBERplot;
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