7085ba0931
nonlinear MLSE investigation trying hard to implment ML-based pre Equalization to find the branch metrics
568 lines
23 KiB
Matlab
568 lines
23 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 = [-6];
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bwl = [0.5:0.1:1.5];
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fsym = [192:16:256].*1e9;
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fsym = 208e9;
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ber_vnle = [];
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ber_mlse = [];
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ber_mlse_burg = [];
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ber_viterbi = [];
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ber_db = [];
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ber_db_diff_precoded = [];
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gmi_vnle_bitwise = [];
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gmi_mlse = [];
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gmi_mlse_db = [];
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for r = 1:length(fsym)
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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*0.5;
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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 0
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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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Opt_sig.eye(fsym(r),M,"fignum",103837);
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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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% Opt_sig.eye(fsym(r),M,"fignum",103838);
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% % Opt_sig.signal = Opt_sig.signal + 5*abs(mean(Opt_sig.signal));
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% Opt_sig.move_it_spectrum("displayname",'Opt Sig after Amp','fignum',1223323);
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% Pc = abs(mean(Opt_sig.signal)).^2; % carrier power
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% Ptot = mean(abs(Opt_sig.signal).^2); % total power
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% Ps = max(Ptot - Pc, eps);
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% Pcdb = 10*log10(Pc);
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% Psdb = 10*log10(Ps);
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%
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% cspr_dB = 10*log10(Pc / Ps);
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%
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% % Minimal in-place CSPR set (real, nonnegative field constraint)
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% E = Opt_sig.signal; % real field samples
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% target_cspr_dB = 20; % <-- set your target CSPR (dB)
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%
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% % Decompose into DC + zero-mean waveform
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% m = mean(E);
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% x0 = E - m; % zero-mean modulation
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% Ps0 = mean(x0.^2); % sideband power (fixed if shape kept)
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%
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% % Current CSPR (for reference)
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% Pc_cur = m^2;
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% Ptot_cur = mean(E.^2);
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% Ps_cur = max(Ptot_cur - Pc_cur, eps);
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% cspr_in = 10*log10(Pc_cur / Ps_cur);
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%
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% % Bias needed for target CSPR, and minimal bias to keep E>=0
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% R_tgt = 10^(target_cspr_dB/10); % Pc/Ps
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% a_req = sqrt(R_tgt * Ps0); % required DC bias
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% a_min = -min(x0); % to avoid negatives everywhere
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% a = max(a_req, a_min); % if infeasible, lands at CSPR_min
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%
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% % Apply bias (preserves waveform shape)
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% E_new = a + x0;
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%
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% % Achieved CSPR
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% Pc_new = mean(E_new)^2;
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% Ptot_new = mean(E_new.^2);
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% Ps_new = max(Ptot_new - Pc_new, eps);
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% cspr_out = 10*log10(Pc_new / Ps_new);
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%
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% % (Optional) show feasibility info
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% cspr_min = 10*log10((a_min^2)/max(Ps0,eps));
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% disp(table(cspr_in, target_cspr_dB, cspr_min, cspr_out));
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%
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% % Use E_new as your adjusted field
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% Opt_sig.signal = E_new;
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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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%Duobinary Targeting
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eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_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);
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db_ref_sequence = Duobinary().encode(Symbols);
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db_ref_constellation = unique(db_ref_sequence.signal);
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[eq_signal, eq_noise] = eq_.process(Rx_sig,db_ref_sequence);
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viterbi = 0;
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if viterbi
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mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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mlse_.DIR = [1,1];
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[eq_signal_whitened] = mlse_.process(eq_signal);
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else
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mlse_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling);
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mlse_.DIR = [1,1];
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[eq_signal_whitened,LLR,gmi_mlse_db(r)] = mlse_.process(eq_signal,Symbols);
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end
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mlse_sig_hd = PAMmapper(M,0,"eth_style",0).quantize(eq_signal_whitened);
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mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
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mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
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tx_symbols_precoded = Duobinary().encode(Symbols);
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tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
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tx_bits_precoded = PAMmapper(M,0,"eth_style",0).demap(tx_symbols_precoded);
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rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd_precoded);
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[~,errors_db_diff_precoded,ber_db_diff_precoded(r),a] = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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burst_db_pre(r,:) = count_error_bursts(a, 15)./numel(Tx_bits.signal);
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%B) Just determine BER
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rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
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[bits_mlse,errors_db,ber_db(r),a] = calc_ber(rx_bits_mlse.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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burst_db(r,:) = count_error_bursts(a, 15)./numel(Tx_bits.signal);
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fprintf('BER ber_db_diff_precoded: %.2e \n',ber_db_diff_precoded(r));
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fprintf('BER Vber_dbNLE: %.2e \n',ber_db(r));
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% figure();hold on;stem(1:15,burst_db(r,:),'LineWidth',1,'Color',cols(1,:));stem(1:15,burst_db_pre(r,:),'LineWidth',1,'Color',cols(2,:));set(gca, 'yscale', 'log');
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end
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% FFE or VNLE
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eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_order3],"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",0.00,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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% eq = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0,"order",[50,2,2],"sps",2,"decide",0);
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[eq_signal_fullresp, eq_noise] = eq_.process(Rx_sig, Symbols);
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showEQNoisePSD(eq_noise, "fignum",1273876,"displayname",'noise after EQ');
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[mi_gomez(r)] = calc_air(eq_signal_fullresp, Symbols, "skip_front", 100, "skip_end", 100);
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[gmi_vnle_bitwise(r)] = calc_ngmi(eq_signal_fullresp,Symbols);
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[gmi_bitwise_2(r)] = calc_gmi_bitwise(eq_signal_fullresp,Symbols);
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snr_vnle(r) = calc_snr(Symbols, eq_signal_fullresp-Symbols);
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% eq_signal_fullresp.plot("displayname",'bla','fignum',199);
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% eq_signal_fullresp.eye(fsym(r),M,"fignum",103837);
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% Hard decision on VNLE output
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eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_fullresp);
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rx_bits = PAMmapper(M,0,"eth_style",0).demap(eq_signal_hd);
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[~,tot_err,ber_vnle(r),a] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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burst_vnle(r,:) = count_error_bursts(a, 10)./tot_err;
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% showLevelConfusionMatrix(eq_signal_hd,Symbols,"M",M,"fignum",200,"displayname",'bla');
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% showLevelScatter(eq_signal_fullresp,Symbols,"displayname",'VNLE Out','f_sym',fsym(r),'fignum',201);
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% show2Dconstellation(eq_signal_fullresp,Symbols,"displayname",'VNLE Out','fignum',2241);
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fprintf('BER VNLE: %.2e \n',ber_vnle(r));
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fprintf('NGMI VNLE: %.2f \n',gmi_vnle_bitwise(r)./m);
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if 1
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% Process through postfilter and MLSE
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pf_ncoeffs = 1;
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if fsym(r) < 200e9
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1,"coefficients",[1,0.1]);
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else
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1,"coefficients",[1,0.85]);
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end
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% showEQNoisePSD(eq_noise,"postfilter_taps",pf_.coefficients,"displayname",'Postfilter Burg based');
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alpha(r) = pf_.coefficients(2);
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alpha_vec = max(0,round(alpha(r),2)-0.2):0.025:round(alpha(r),2)+0.4;
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alpha_vec = unique(sort([alpha_vec, 1, alpha(r)]));
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gmi_mlse_ = zeros(size(alpha_vec));
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ber_mlse_ = zeros(size(alpha_vec));
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parfor a=1:numel(alpha_vec)
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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling,'DIR',[1,alpha_vec(a)]);
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pf_ = Postfilter("ncoeff",1,"useBurg",0,"coefficients",[1,alpha_vec(a)]);
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[eq_signal_whitened,whitened_noise] = pf_.process(eq_signal_fullresp, eq_noise);
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[signalclass_hd,LLR,gmi_mlse_(a)] = mlse_.process(eq_signal_whitened,Symbols);
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mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(signalclass_hd);
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rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
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[~,tot_err,ber_mlse_(a),errpos] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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% burst_mlse(r,:) = count_error_bursts(errpos, 10);
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% if 0
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% fprintf('BER MLSE: %.2e \n',ber_mlse(r));
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% fprintf('NGMI MLSE: %.5f \n',gmi_mlse(r)./m);
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%
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% showLevelConfusionMatrix(mlse_sig_hd,Symbols,"M",M,"fignum",300,"displayname",'bla');
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%
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% levels = sort(unique(Symbols.signal(:)).'); % 1×6
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% pairs = reshape(mlse_sig_hd.signal,2,[]).';
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% isedge = ismember(pairs, [levels(1) levels(end)]);
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% isforbidden = sum(isedge,2)==2;
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% fprintf('Found %d forbidden transitions (even→odd edges).\n', nnz(isforbidden));
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%
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%
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% % Process through postfilter and MLSE
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% pf_ncoeffs = 1;
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% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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% mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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% [eq_signal_whitened,whitened_noise] = pf_.process(eq_signal_fullresp, eq_noise);
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% mlse_.DIR = pf_.coefficients;
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% mlse_output = mlse_.process(eq_signal_whitened);
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% mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(mlse_output);
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% rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
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% [~,~,ber_viterbi(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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% fprintf('Viterbi BER: %.2e \n',ber_viterbi(r));
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% end
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end
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[ber_mlse(r),idx] = min(ber_mlse_);
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gmi_mlse(r) = gmi_mlse_(idx);
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ber_mlse_burg(r) = ber_mlse_(alpha_vec==alpha(r));
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best_alpha(r) = alpha_vec(idx);
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end
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% IR target in EQ
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if 1
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% alpha_vec = max(0,round(alpha(r),2)-0.1):0.01:min(1,round(alpha(r),2)+0.1);
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plot_stuff = 0;
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gmi_mlse_pr_tgt_ = zeros(size(alpha_vec));
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ber_mlse_pr_tgt_ = zeros(size(alpha_vec));
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parfor a = 1:numel(alpha_vec)
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eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_order3],"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",0.00,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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Symbols_filt = Symbols.filter([1,alpha_vec(a)],1);
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[eq_signal_prtgt, eq_noise] = eq_.process(Rx_sig, Symbols_filt);
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if plot_stuff
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% Plot the response for respective EQ targets
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Symbols_filt.spectrum("displayname",'IDEAL Filtered Reference','fignum',240587);
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eq_signal_whitened.spectrum("displayname",'Full tgt. EQ + PF','fignum',240587);
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eq_signal_prtgt.spectrum("displayname",'Partial Resp. Target EQ','fignum',240587);
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noise_pf_out = Symbols_filt-eq_signal_whitened;
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noise_pr_tgt = Symbols_filt-eq_signal_prtgt;
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noise_pf_out.spectrum("displayname",'Ideal PR - Whitening Out','fignum',240588);
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noise_pr_tgt.spectrum("displayname",'Ideal PR - PR Target Out','fignum',240588);
|
||
end
|
||
|
||
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling,'DIR',[1,alpha_vec(a)],'debug',0);
|
||
|
||
[signalclass_hd,LLR,gmi_mlse_pr_tgt_(a)] = mlse_.process(eq_signal_prtgt,Symbols);
|
||
|
||
mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(signalclass_hd);
|
||
|
||
rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
|
||
|
||
[~,tot_err,ber_mlse_pr_tgt_(a),errpos] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||
|
||
% burst_mlse_(a,:) = count_error_bursts(errpos, 10);
|
||
|
||
% fprintf('BER MLSE: %.2e \n',ber_mlse_pr_tgt_(a));
|
||
% fprintf('NGMI MLSE: %.5f \n',gmi_mlse_pr_tgt_(a)./m);
|
||
|
||
end
|
||
|
||
[ber_mlse_pr_tgt(r),idx] = min(ber_mlse_pr_tgt_);
|
||
gmi_mlse_pr_tgt(r) = gmi_mlse_pr_tgt_(idx);
|
||
best_alpha_pr_tgt(r) = alpha_vec(idx);
|
||
|
||
end
|
||
|
||
|
||
cols = cbrewer2('paired',8);
|
||
figure(); hold on
|
||
title(sprintf('%d GBd',fsym(r).*1e-9));
|
||
scatter(alpha_vec,ber_mlse_,15,'Marker','o','LineWidth',1,'DisplayName','MLSE','MarkerEdgeColor',cols(1,:));
|
||
scatter(best_alpha(r),ber_mlse(r),15,'Marker','o','LineWidth',2,'DisplayName','MLSE','MarkerEdgeColor',cols(2,:));
|
||
scatter(alpha(r),ber_mlse_burg(r),25,'Marker','+','LineWidth',2,'DisplayName','MLSE','MarkerEdgeColor',cols(2,:));
|
||
|
||
scatter(1,ber_db_diff_precoded(r),15,'Marker','diamond','LineWidth',2,'DisplayName','Duobinary','MarkerEdgeColor',cols(4,:));
|
||
scatter(1,ber_db(r),15,'Marker','diamond','LineWidth',2,'DisplayName','Duobinary','MarkerEdgeColor',cols(4,:));
|
||
|
||
scatter(alpha_vec,ber_mlse_pr_tgt_,15,'Marker','x','LineWidth',1,'DisplayName','MLSE Partial Resp tgt','MarkerEdgeColor',cols(5,:));
|
||
scatter(best_alpha_pr_tgt(r),ber_mlse_pr_tgt(r),25,'Marker','x','LineWidth',2,'DisplayName','MLSE','MarkerEdgeColor',cols(6,:));
|
||
|
||
set(gca,"YScale","log");
|
||
% ylim([1e-6 0.5]);
|
||
% xlim([0.1 1]);
|
||
drawnow;
|
||
|
||
|
||
|
||
end
|
||
|
||
|
||
|
||
|
||
% --- style control (one variable controls both marker size and linewidth) ---
|
||
STYLE_BASE = 2; % adjust this single number to scale markers & lines
|
||
MARKER_SIZE = STYLE_BASE; % marker size (MATLAB MarkerSize)
|
||
LINE_WIDTH = max(1.5, STYLE_BASE/3); % line width (keeps lines reasonable when STYLE_BASE large)
|
||
|
||
% --- color map / method -> color assignment (keeps colors consistent) ---
|
||
cols = cbrewer2('Paired',8);
|
||
cols = linspecer(6);
|
||
d = 0;
|
||
cm.VNLE = cols(1 + d, :);
|
||
cm.MLSE = cols(2 + d, :);
|
||
cm.DB_precode = cols(3 + d, :);
|
||
cm.DB = cols(4 + d, :); % duobinary
|
||
|
||
% prepare x values in GBd
|
||
xGHz = fsym .* 1e-9;
|
||
xticks_vals = xGHz;
|
||
xtick_labels = arrayfun(@(v) sprintf('%d', round(v)), xticks_vals, 'UniformOutput', false);
|
||
|
||
% common marker settings (filled, same face+edge color)
|
||
mk.VNLE = {'Marker','none','MarkerFaceColor',cm.MLSE,'MarkerEdgeColor',cm.VNLE,'MarkerSize',MARKER_SIZE};
|
||
mk.MLSE = {'Marker','none','MarkerFaceColor',cm.MLSE,'MarkerEdgeColor',cm.MLSE,'MarkerSize',MARKER_SIZE};
|
||
mk.DB_precode = {'Marker','none','MarkerFaceColor',cm.DB_precode,'MarkerEdgeColor',cm.DB_precode,'MarkerSize',MARKER_SIZE};
|
||
mk.DB = {'Marker','none','MarkerFaceColor',cm.DB,'MarkerEdgeColor',cm.DB,'MarkerSize',MARKER_SIZE};
|
||
|
||
% ---------------- FIGURE 11 : alpha (VNLE) ----------------
|
||
figure(110+M); clf; hold on;
|
||
plot(xGHz, alpha, ...
|
||
'DisplayName','VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
xlabel('Baudrate in GBd');
|
||
ylabel('alpha');
|
||
set(gca, 'XTick', xticks_vals, 'XTickLabel', xtick_labels);
|
||
grid on;
|
||
legend('Location','best');
|
||
|
||
% ---------------- FIGURE 15 : GMI ----------------
|
||
figure(111+M); clf; hold on;
|
||
plot(xGHz, mi_gomez, ...
|
||
'DisplayName','MI VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
plot(xGHz, gmi_vnle_bitwise, ...
|
||
'DisplayName','GMI VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
% duobinary has only one GMI curve (DB output)
|
||
plot(xGHz, gmi_mlse_db, ...
|
||
'DisplayName','GMI DB tgt.', ...
|
||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
% MLSE symbol-wise (if present)
|
||
plot(xGHz, gmi_mlse, ...
|
||
'DisplayName','GMI MLSE', ...
|
||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
|
||
ylim([log2(M)-1, log2(M)]);
|
||
xlabel('Baudrate in GBd');
|
||
ylabel('GMI');
|
||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||
grid on;
|
||
legend('Location','best');
|
||
% xlim([184, 256])
|
||
|
||
% ---------------- FIGURE 13 : BER ----------------
|
||
figure(312+M); hold on;
|
||
plot(xGHz, ber_vnle, ...
|
||
'DisplayName','VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
plot(xGHz, ber_mlse, ...
|
||
'DisplayName','MLSE', ...
|
||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
plot(xGHz, ber_viterbi, ...
|
||
'DisplayName','Viterbi', ...
|
||
mk.MLSE{:}, 'LineStyle','--','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
|
||
yline(4.85e-3,'LineWidth',1,'HandleVisibility','off');
|
||
yline(2.2e-4,'LineWidth',1,'HandleVisibility','off');
|
||
|
||
plot(xGHz, ber_db, ...
|
||
'DisplayName','DB tgt.', ...
|
||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
|
||
plot(xGHz, ber_db_diff_precoded, ...
|
||
'DisplayName','Prec. + DB tgt.', ...
|
||
mk.DB{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
|
||
xlabel('Baudrate in GBd');
|
||
ylabel('BER');
|
||
set(gca, 'yscale', 'log');
|
||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||
grid on;
|
||
legend('Location','best');
|
||
% xlim([184, 256])
|
||
|
||
% ---------------- FIGURE 15 : Information Rates ----------------
|
||
tp = TransmissionPerformance;
|
||
|
||
|
||
m = floor(log2(M)*10)/10;
|
||
figure(113+M); clf; hold on;
|
||
|
||
netrates_vnle = tp.calculateNetRate(fsym.* m, ...
|
||
'NGMI', gmi_vnle_bitwise./m, ...
|
||
'BER', ber_vnle);
|
||
%
|
||
plot(xGHz, gmi_vnle_bitwise.*xGHz, ...
|
||
'DisplayName','GMI*R VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
|
||
plot(xGHz, netrates_vnle.SDHD.NetRate.*1e-9, ...
|
||
'DisplayName','SD+HD VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
plot(xGHz, netrates_vnle.HD.NetRate.*1e-9, ...
|
||
'DisplayName','Staircase VNLE', ...
|
||
mk.VNLE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||
|
||
|
||
%
|
||
% MLSE symbol-wise (if present)
|
||
plot(xGHz, gmi_mlse.*xGHz, ...
|
||
'DisplayName','GMI*R MLSE', ...
|
||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
|
||
netrates_mlse = tp.calculateNetRate(fsym.* m, ...
|
||
'NGMI', gmi_mlse./m, ...
|
||
'BER', ber_mlse);
|
||
plot(xGHz, netrates_mlse.SDHD.NetRate.*1e-9, ...
|
||
'DisplayName','SD+HD MLSE', ...
|
||
mk.MLSE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
plot(xGHz, netrates_mlse.HD.NetRate.*1e-9, ...
|
||
'DisplayName','Staircase MLSE', ...
|
||
mk.MLSE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||
|
||
|
||
% duobinary has only one GMI curve (DB output)
|
||
plot(xGHz, gmi_mlse_db.*xGHz, ...
|
||
'DisplayName','GMI*R DB tgt.', ...
|
||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
|
||
netrates_db = tp.calculateNetRate(fsym.* m, ...
|
||
'NGMI', gmi_mlse_db./m, ...
|
||
'BER', ber_db);
|
||
|
||
plot(xGHz, netrates_db.SDHD.NetRate.*1e-9, ...
|
||
'DisplayName','SD+HD DB', ...
|
||
mk.DB{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
plot(xGHz, netrates_db.HD.NetRate.*1e-9, ...
|
||
'DisplayName','Staircase DB', ...
|
||
mk.DB{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||
|
||
|
||
|
||
% ylim([log2(M)-1, log2(M)]);
|
||
xlabel('Baudrate in GBd');
|
||
ylabel('AIR in Gbps');
|
||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||
grid on;
|
||
legend('Location','best');
|
||
xlim([184, 256])
|
||
|
||
% Auxiliary nested helper for numerically stable log-sum-exp
|
||
function s = logsumexp(a)
|
||
% LOGSUMEXP Compute log(sum(exp(a))) in a numerically stable way
|
||
m = max(a);
|
||
s = m + log(sum(exp(a - m)));
|
||
end
|