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Gif stuff

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nonlinear MLSE investigation
trying hard to implment ML-based pre Equalization to find the branch metrics
This commit is contained in:
Silas Oettinghaus
2025-10-24 16:58:06 +02:00
parent c33264a515
commit 7085ba0931
16 changed files with 1414 additions and 162 deletions
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16
projects/HighSpeedExperiment_2024/Auswertung_JLT/run_dsp_from_db.m
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@@ -40,18 +40,18 @@ end
fp = QueryFilter();
% fp.where('Runs', 'run_id','EQUALS', 987);
M = 6;
% fp.where('Runs', 'pam_level','EQUALS', M);
% fp.where('Runs', 'bitrate','EQUALS', 480e9);
M = 4;
fp.where('Runs', 'pam_level','EQUALS', M);
fp.where('Runs', 'bitrate','EQUALS', 420e9);%360,390
% fp.where('Runs', 'symbolrate','EQUALS', 162e9);
% fp.where('Runs', 'fiber_length','EQUALS', 1);
fp.where('Runs', 'fiber_length','EQUALS', 2);
fp.where('Runs', 'is_mpi','EQUALS', 0);
% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
% fp.where('Runs', 'sir','EQUALS',18);
fp.where('Runs', 'wavelength','LESS_THAN', 1311);
% fp.where('Runs', 'db_mode','EQUALS', 0);
% fp.where('Runs', 'rop_attenuation','NOT_EQUAL', 0);
fp.where('Runs', 'wavelength','EQUAL', 1310);
fp.where('Runs', 'db_mode','EQUALS', 0);
fp.where('Runs', 'rop_attenuation','EQUAL', 0);
% fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
@@ -69,7 +69,7 @@ wh.addStorage("dbenc_package");
% === RUN IT ===
[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "parallel", 'wh', wh, 'waitbar', true);
[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "serial", 'wh', wh, 'waitbar', true);
results_db = results(dataTable.db_mode==1);
results_nodb = results(dataTable.db_mode==0);

2
projects/HighSpeedExperiment_2024/Auswertung_JLT/run_plot_measurements.m
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@@ -6,7 +6,7 @@ M = 4;
fp = QueryFilter();
% fp.where('Runs', 'run_id','EQUALS', 987);
fp.where('Runs', 'pam_level','EQUALS', M);
fp.where('Runs', 'symbolrate','EQUALS', 150e9);
% fp.where('Runs', 'symbolrate','EQUALS', 150e9);
% fp.where('Runs', 'fiber_length','EQUALS', 10);
fp.where('Runs', 'is_mpi','EQUALS', 0);
% fp.where('Runs', 'interference_path_length','EQUALS', 1000);

286
projects/IMDD_base_system/simulation_bwl.m
View File

@@ -47,16 +47,17 @@ doub_mode = db_mode.no_db;
cols = linspecer(6);
rop = [-6];
bwl = [0.5:0.1:1.5];
fsym = [120:8:256].*1e9;
fsym =210e9;
fsym = [192:16:256].*1e9;
fsym = 208e9;
ber_vnle = [];
ber_vnle = [];
ber_mlse = [];
ber_mlse_burg = [];
ber_viterbi = [];
ber_db = [];
ber_db_diff_precoded = [];
gmi_vnle_bitwise = [];
gmi_mlse = [];
gmi_mlse = [];
gmi_mlse_db = [];
for r = 1:length(fsym)
@@ -69,16 +70,16 @@ for r = 1:length(fsym)
apply_pulsef = 1;
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
"fsym",fsym(r),"M",M,"order",18,"useprbs",0,...
"fsym",fsym(r),"M",M,"order",19,"useprbs",0,...
"fs_out",fdac,...
"applyclipping",0,"clipfactor",1.5,...
"applypulseform",apply_pulsef,"pulseformer",Pform,...
"randkey",random_key,...
"db_precode",db_precode,"db_encode",db_encode,...
"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
% 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);
El_sig = M8199B("kover",kover).process(Digi_sig);
El_sig = M8199B("kover",kover).process(Digi_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);
%%%%% Low-pass el. components %%%%%%
@@ -95,15 +96,17 @@ for r = 1:length(fsym)
vbias = -u_pi*0.5;
[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);
figure(15);
hold on
scatter(El_sig.signal(1:100000)+vbias,(abs(Opt_sig.signal(1:100000)).^2)*1e3,0.1,'.','DisplayName','Modulator TF')
xlabel('Input in V')
ylabel('abs(Eopt)2 in mW','Interpreter','latex')
ylim([0 2]);
xlim([-3.2 0]);
Opt_sig.eye(fsym(r),M,"fignum",103837);
if 0
figure(15);
hold on
scatter(El_sig.signal(1:100000)+vbias,(abs(Opt_sig.signal(1:100000)).^2)*1e3,0.1,'.','DisplayName','Modulator TF')
xlabel('Input in V')
ylabel('abs(Eopt)2 in mW','Interpreter','latex')
ylim([0 2]);
xlim([-3.2 0]);
Opt_sig.eye(fsym(r),M,"fignum",103837);
end
%%%%%% Fiber %%%%%%
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);
@@ -113,50 +116,50 @@ for r = 1:length(fsym)
% Opt_sig.eye(fsym(r),M,"fignum",103838);
% % Opt_sig.signal = Opt_sig.signal + 5*abs(mean(Opt_sig.signal));
% % Opt_sig.signal = Opt_sig.signal + 5*abs(mean(Opt_sig.signal));
% Opt_sig.move_it_spectrum("displayname",'Opt Sig after Amp','fignum',1223323);
% Pc = abs(mean(Opt_sig.signal)).^2; % carrier power
% Ptot = mean(abs(Opt_sig.signal).^2); % total power
% Ps = max(Ptot - Pc, eps);
% Ps = max(Ptot - Pc, eps);
% Pcdb = 10*log10(Pc);
% Psdb = 10*log10(Ps);
%
%
% cspr_dB = 10*log10(Pc / Ps);
%
%
% % Minimal in-place CSPR set (real, nonnegative field constraint)
% E = Opt_sig.signal; % real field samples
% target_cspr_dB = 20; % <-- set your target CSPR (dB)
%
%
% % Decompose into DC + zero-mean waveform
% m = mean(E);
% x0 = E - m; % zero-mean modulation
% Ps0 = mean(x0.^2); % sideband power (fixed if shape kept)
%
%
% % Current CSPR (for reference)
% Pc_cur = m^2;
% Ptot_cur = mean(E.^2);
% Ps_cur = max(Ptot_cur - Pc_cur, eps);
% cspr_in = 10*log10(Pc_cur / Ps_cur);
%
%
% % Bias needed for target CSPR, and minimal bias to keep E>=0
% R_tgt = 10^(target_cspr_dB/10); % Pc/Ps
% a_req = sqrt(R_tgt * Ps0); % required DC bias
% a_min = -min(x0); % to avoid negatives everywhere
% a = max(a_req, a_min); % if infeasible, lands at CSPR_min
%
%
% % Apply bias (preserves waveform shape)
% E_new = a + x0;
%
%
% % Achieved CSPR
% Pc_new = mean(E_new)^2;
% Ptot_new = mean(E_new.^2);
% Ps_new = max(Ptot_new - Pc_new, eps);
% cspr_out = 10*log10(Pc_new / Ps_new);
%
%
% % (Optional) show feasibility info
% cspr_min = 10*log10((a_min^2)/max(Ps0,eps));
% disp(table(cspr_in, target_cspr_dB, cspr_min, cspr_out));
%
%
% % Use E_new as your adjusted field
% Opt_sig.signal = E_new;
@@ -166,57 +169,56 @@ for r = 1:length(fsym)
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
rx_bwl = 70e9;
PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig);
% %%%%%% Low-pass Scope %%%%%%
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
%%%%%% Scope %%%%%%
Scpe_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(PD_sig);
Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym(r));
% Scpe_sig_resampled.signal = Scpe_sig_resampled.signal(1:2*length(Symbols));
[~, Scpe_cell, ~, found_sync] = Scpe_sig_2sps.tsynch("reference", Symbols, "fs_ref", fsym(r), "debug_plots", 0);
Rx_sig = Scpe_cell{1};
Rx_sig = Rx_sig.normalize("mode","rms");
if 0
if 1
%Duobinary Targeting
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);
db_ref_sequence = Duobinary().encode(Symbols);
db_ref_constellation = unique(db_ref_sequence.signal);
[eq_signal, eq_noise] = eq_.process(Rx_sig,db_ref_sequence);
viterbi = 0;
if viterbi
if viterbi
mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
mlse_.DIR = [1,1];
[mlse_sig_sd] = mlse_.process(eq_signal);
[eq_signal_whitened] = mlse_.process(eq_signal);
else
mlse_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling);
mlse_.DIR = [1,1];
[mlse_sig_sd,LLR,gmi_mlse_db(r)] = mlse_.process(eq_signal,Symbols);
[eq_signal_whitened,LLR,gmi_mlse_db(r)] = mlse_.process(eq_signal,Symbols);
end
mlse_sig_hd = PAMmapper(M,0,"eth_style",0).quantize(mlse_sig_sd);
mlse_sig_hd = PAMmapper(M,0,"eth_style",0).quantize(eq_signal_whitened);
mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
tx_symbols_precoded = Duobinary().encode(Symbols);
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
tx_bits_precoded = PAMmapper(M,0,"eth_style",0).demap(tx_symbols_precoded);
rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd_precoded);
[~,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);
burst_db_pre(r,:) = count_error_bursts(a, 15)./numel(Tx_bits.signal);
%B) Just determine BER
rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
[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);
@@ -225,39 +227,37 @@ for r = 1:length(fsym)
fprintf('BER ber_db_diff_precoded: %.2e \n',ber_db_diff_precoded(r));
fprintf('BER Vber_dbNLE: %.2e \n',ber_db(r));
% 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');
end
% FFE or VNLE
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);
% 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);
[eq_signal_sd, eq_noise] = eq_.process(Rx_sig, Symbols);
[eq_signal_fullresp, eq_noise] = eq_.process(Rx_sig, Symbols);
showEQNoisePSD(eq_noise, "fignum",1273876,"displayname",'noise after EQ');
[mi_gomez(r)] = calc_air(eq_signal_sd, Symbols, "skip_front", 100, "skip_end", 100);
[gmi_vnle_bitwise(r)] = calc_ngmi(eq_signal_sd,Symbols);
[gmi_bitwise_2(r)] = calc_gmi_bitwise(eq_signal_sd,Symbols);
snr_vnle(r) = calc_snr(Symbols, eq_signal_sd-Symbols);
eq_signal_sd.plot("displayname",'bla','fignum',199);
eq_signal_sd.eye(fsym(r),M,"fignum",103837);
[mi_gomez(r)] = calc_air(eq_signal_fullresp, Symbols, "skip_front", 100, "skip_end", 100);
[gmi_vnle_bitwise(r)] = calc_ngmi(eq_signal_fullresp,Symbols);
[gmi_bitwise_2(r)] = calc_gmi_bitwise(eq_signal_fullresp,Symbols);
snr_vnle(r) = calc_snr(Symbols, eq_signal_fullresp-Symbols);
% eq_signal_fullresp.plot("displayname",'bla','fignum',199);
% eq_signal_fullresp.eye(fsym(r),M,"fignum",103837);
% Hard decision on VNLE output
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_fullresp);
rx_bits = PAMmapper(M,0,"eth_style",0).demap(eq_signal_hd);
[~,tot_err,ber_vnle(r),a] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
burst_vnle(r,:) = count_error_bursts(a, 10)./tot_err;
showLevelConfusionMatrix(eq_signal_hd,Symbols,"M",M,"fignum",200,"displayname",'bla');
showLevelScatter(eq_signal_sd,Symbols,"displayname",'VNLE Out','f_sym',fsym(r),'fignum',201);
show2Dconstellation(eq_signal_sd,Symbols,"displayname",'VNLE Out','fignum',2241);
% showLevelConfusionMatrix(eq_signal_hd,Symbols,"M",M,"fignum",200,"displayname",'bla');
% showLevelScatter(eq_signal_fullresp,Symbols,"displayname",'VNLE Out','f_sym',fsym(r),'fignum',201);
% show2Dconstellation(eq_signal_fullresp,Symbols,"displayname",'VNLE Out','fignum',2241);
fprintf('BER VNLE: %.2e \n',ber_vnle(r));
fprintf('NGMI VNLE: %.2f \n',gmi_vnle_bitwise(r)./m);
if 1
% Process through postfilter and MLSE
@@ -268,45 +268,133 @@ for r = 1:length(fsym)
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1,"coefficients",[1,0.85]);
end
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling);
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
mlse_.DIR = pf_.coefficients;
% showEQNoisePSD(eq_noise,"postfilter_taps",pf_.coefficients,"displayname",'Postfilter Burg based');
alpha(r) = pf_.coefficients(2);
[signalclass_hd,LLR,gmi_mlse(r)] = mlse_.process(mlse_sig_sd,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);
alpha_vec = max(0,round(alpha(r),2)-0.2):0.025:round(alpha(r),2)+0.4;
alpha_vec = unique(sort([alpha_vec, 1, alpha(r)]));
[~,tot_err,ber_mlse(r),a] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
burst_mlse(r,:) = count_error_bursts(a, 10);
gmi_mlse_ = zeros(size(alpha_vec));
ber_mlse_ = zeros(size(alpha_vec));
parfor a=1:numel(alpha_vec)
showLevelConfusionMatrix(mlse_sig_hd,Symbols,"M",M,"fignum",300,"displayname",'bla');
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).get_levels ./ PAMmapper(M,0).get_scaling,'DIR',[1,alpha_vec(a)]);
fprintf('BER MLSE: %.2e \n',ber_mlse(r));
fprintf('NGMI MLSE: %.5f \n',gmi_mlse(r)./m);
pf_ = Postfilter("ncoeff",1,"useBurg",0,"coefficients",[1,alpha_vec(a)]);
[eq_signal_whitened,whitened_noise] = pf_.process(eq_signal_fullresp, eq_noise);
[signalclass_hd,LLR,gmi_mlse_(a)] = mlse_.process(eq_signal_whitened,Symbols);
levels = sort(unique(Symbols.signal(:)).'); % 1×6
pairs = reshape(mlse_sig_hd.signal,2,[]).';
isedge = ismember(pairs, [levels(1) levels(end)]);
isforbidden = sum(isedge,2)==2;
fprintf('Found %d forbidden transitions (even→odd edges).\n', nnz(isforbidden));
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_(a),errpos] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% burst_mlse(r,:) = count_error_bursts(errpos, 10);
% if 0
% fprintf('BER MLSE: %.2e \n',ber_mlse(r));
% fprintf('NGMI MLSE: %.5f \n',gmi_mlse(r)./m);
%
% showLevelConfusionMatrix(mlse_sig_hd,Symbols,"M",M,"fignum",300,"displayname",'bla');
%
% levels = sort(unique(Symbols.signal(:)).'); % 1×6
% pairs = reshape(mlse_sig_hd.signal,2,[]).';
% isedge = ismember(pairs, [levels(1) levels(end)]);
% isforbidden = sum(isedge,2)==2;
% fprintf('Found %d forbidden transitions (even→odd edges).\n', nnz(isforbidden));
%
%
% % Process through postfilter and MLSE
% pf_ncoeffs = 1;
% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
% mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
% [eq_signal_whitened,whitened_noise] = pf_.process(eq_signal_fullresp, eq_noise);
% mlse_.DIR = pf_.coefficients;
% mlse_output = mlse_.process(eq_signal_whitened);
% mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(mlse_output);
% rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
% [~,~,ber_viterbi(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% fprintf('Viterbi BER: %.2e \n',ber_viterbi(r));
% end
end
[ber_mlse(r),idx] = min(ber_mlse_);
gmi_mlse(r) = gmi_mlse_(idx);
ber_mlse_burg(r) = ber_mlse_(alpha_vec==alpha(r));
best_alpha(r) = alpha_vec(idx);
end
% IR target in EQ
if 1
% alpha_vec = max(0,round(alpha(r),2)-0.1):0.01:min(1,round(alpha(r),2)+0.1);
plot_stuff = 0;
gmi_mlse_pr_tgt_ = zeros(size(alpha_vec));
ber_mlse_pr_tgt_ = zeros(size(alpha_vec));
parfor a = 1:numel(alpha_vec)
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);
Symbols_filt = Symbols.filter([1,alpha_vec(a)],1);
[eq_signal_prtgt, eq_noise] = eq_.process(Rx_sig, Symbols_filt);
% Process through postfilter and MLSE
pf_ncoeffs = 1;
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
mlse_.DIR = pf_.coefficients;
mlse_sig_sd = mlse_.process(mlse_sig_sd);
mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(mlse_sig_sd);
rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
[~,~,ber_viterbi(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('Viterbi BER: %.2e \n',ber_viterbi(r));
if plot_stuff
% Plot the response for respective EQ targets
Symbols_filt.spectrum("displayname",'IDEAL Filtered Reference','fignum',240587);
eq_signal_whitened.spectrum("displayname",'Full tgt. EQ + PF','fignum',240587);
eq_signal_prtgt.spectrum("displayname",'Partial Resp. Target EQ','fignum',240587);
noise_pf_out = Symbols_filt-eq_signal_whitened;
noise_pr_tgt = Symbols_filt-eq_signal_prtgt;
noise_pf_out.spectrum("displayname",'Ideal PR - Whitening Out','fignum',240588);
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
@@ -413,9 +501,9 @@ 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);
%
'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);
@@ -428,15 +516,15 @@ plot(xGHz, netrates_vnle.HD.NetRate.*1e-9, ...
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);
'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);
@@ -451,8 +539,8 @@ plot(xGHz, gmi_mlse_db.*xGHz, ...
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
netrates_db = tp.calculateNetRate(fsym.* m, ...
'NGMI', gmi_mlse_db./m, ...
'BER', ber_db);
'NGMI', gmi_mlse_db./m, ...
'BER', ber_db);
plot(xGHz, netrates_db.SDHD.NetRate.*1e-9, ...
'DisplayName','SD+HD DB', ...
@@ -473,7 +561,7 @@ 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)));
% LOGSUMEXP Compute log(sum(exp(a))) in a numerically stable way
m = max(a);
s = m + log(sum(exp(a - m)));
end

8
projects/IMDD_base_system/simulation_bwl_2.m
View File

@@ -136,9 +136,5 @@ eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
% Process through postfilter and MLSE
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
mlse_.DIR = pf_.coefficients;
constellation = [-3, -1, 1, 3];
chatgpt_answer(mlse_sig_sd.signal, Symbols.signal,mlse_.DIR,constellation);
% mlse_sig_sd = mlse_.process(mlse_sig_sd,Symbols);
% mlse_sig_hd = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
mlse_sig_sd = mlse_.process(mlse_sig_sd,Symbols);
mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(mlse_sig_sd);

194
projects/ML_based_MLSE/model.m Normal file
View File

@@ -0,0 +1,194 @@
%%% Run parameters
% TX
M = 4;
apply_pulsef = 1;
fdac = 256e9;
fadc = 256e9;
random_key = 2;
rcalpha = 0.05;
kover = 8;
vbias_rel = 0.5;
u_pi = 3.2;
vbias = -vbias_rel*u_pi;
laser_wavelength = 1310;
laser_linewidth = 1e6;
% Channel
link_length = 0;
alpha = 0;
doub_mode = db_mode.no_db;
cols = linspecer(6);
rop = [-6];
bwl = [0.5:0.1:1.5];
fsym = [208:16:256].*1e9;
% nonlin_mod = [0.5:0.01:0.75];
nonlin_mod = ones(size(fsym)).*0.5;
ffe_results = {};
mlse_results_lin= {};
for r = 1:length(fsym)
Pform = Pulseformer("fsym",fsym(r),"fdac",4*fsym(r),"pulse","rc","pulselength",16,"alpha",rcalpha);
db_precode = 0;
db_encode = 0;
duob_mode = db_mode.no_db;
apply_pulsef = 1;
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
"fsym",fsym(r),"M",M,"order",17,"useprbs",0,...
"fs_out",fdac,...
"applyclipping",0,"clipfactor",1.5,...
"applypulseform",apply_pulsef,"pulseformer",Pform,...
"randkey",random_key,...
"db_precode",db_precode,"db_encode",db_encode,...
"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
El_sig = M8199B("kover",kover).process(Digi_sig);
%%%%% Electrical Driver Amplifier %%%%%%
El_sig = El_sig.normalize("mode","oneone");
%%%%% MODULATE E/O CONVERSION %%%%%
u_pi = 3.2;
vbias = -u_pi*nonlin_mod(r);
[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);
%%%%%% Fiber %%%%%%
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);
%%%%%% ROP %%%%%%
Opt_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
%%%%%% PD Square Law %%%%%%
PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",random_key).process(Opt_sig);
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
rx_bwl = 70e9;
PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig);
% %%%%%% Low-pass Scope %%%%%%
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
%%%%%% Scope %%%%%%
Scpe_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(PD_sig);
Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym(r));
% 2sps
[~, Scpe_cell, ~, found_sync] = Scpe_sig_2sps.tsynch("reference", Symbols, "fs_ref", fsym(r), "debug_plots", 1);
Rx_sig_2sps = Scpe_cell{1};
Rx_sig_2sps = Rx_sig_2sps.normalize("mode","rms");
% 1sps
Scpe_sig_1sps = Scpe_sig.resample("fs_out",1*fsym(r));
[~, Scpe_cell_1sps, ~, found_sync] = Scpe_sig_1sps.tsynch("reference", Symbols, "fs_ref", fsym(r), "debug_plots", 1);
Rx_sig_1sps = Scpe_cell_1sps{1};
Rx_sig_1sps = Rx_sig_1sps.normalize("mode","rms");
%% Implement DSP directly here:
mu_lms = 0.0005;
tic
eq = ML_MLSE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",2,"traceback_depth",32,"L",1);
[Eq_signal,Vit_signal] = eq.process(Rx_sig_2sps,Symbols);
toc
% tic
% eq = FFE_MLSE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",2,"traceback_depth",32,"L",3);
% [Eq_signal,Vit_signal] = eq.process(Rx_sig_2sps,Symbols);
% toc
Eq_bits = PAMmapper(M, 0, "eth_style", 0).demap(Eq_signal);
[~, errors, ber, ~] = calc_ber(Eq_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
fprintf('FFE: %.2e \n',ber);
Vit_signal_ = Vit_signal;
Vit_signal_.signal = circshift(Vit_signal.signal,0);
Vit_bits = PAMmapper(M, 0, "eth_style", 0).demap(Vit_signal_);
[~, errors, ber, errpos] = calc_ber(Vit_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
fprintf('Viterbi: %.2e \n',ber);
%% optimize smth.
tr_len = 2.^[2:15];
tr_len = floor(tr_len);
ber = zeros(size(tr_len));
parfor m = 1:numel(tr_len)
mu_lms = 0.0005;
eq = ML_MLSE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",2,"traceback_depth",tr_len(m));
[Eq_signal,Vit_signal] = eq.process(Rx_sig_2sps,Symbols);
% Eq_bits = PAMmapper(M, 0, "eth_style", 0).demap(Eq_signal);
% [~, errors, ber(m), ~] = calc_ber(Eq_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
Vit_bits = PAMmapper(M, 0, "eth_style", 0).demap(Vit_signal);
[~, errors, ber(m), errpos] = calc_ber(Vit_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
end
figure(5); hold on
title('1-SPS')
plot(tr_len,ber,'DisplayName','BER');
xlabel('Traceback Length')
beautifyBERplot
legend
ylim([1e-4, 1e-1]);
set(gca,'YScale','log');
%% RUN Comparison
len_tr = 4096*2;
mu_ffe1 = 0.0001;
mu_ffe2 = 0.0008;
mu_ffe3 = 0.001;
mu_dc = 0.005;
% mu_dc = 0;
mu_ffe = [mu_ffe1 mu_ffe2 mu_ffe3];
mu_dfe = 0.0004;
pf_ncoeffs = 1;
ffe_order = [50, 0, 0];
mu_lms = 0.0005;
eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",1,"dd_mode",1,"adaption_technique","lms");
% eq_ = EQ("Ne",ffe_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",1,"DCmu",0.00,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels,'scale_mode',0,'trellis_exclusion',0,'trellis_state_mode',2,'debug',0);
[ffe_results{r}, mlse_results_lin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig_1sps, Symbols, Tx_bits, ...
"precode_mode", duob_mode,...
'showAnalysis', 0, ...
"postFFE", [],...
"eth_style_symbol_mapping", 0);
mlse_results_lin{r}.metrics.print;
ffe_results{r}.metrics.print;
end

229
projects/Nonlinear_MLSE/simulation_nonlin_dsp.m Normal file
View File

@@ -0,0 +1,229 @@
%%% Run parameters
% TX
M = 4;
m = floor(log2(M)*10)/10;
fsym = 224e9;
apply_pulsef = 1;
fdac = 256e9;
fadc = 256e9;
random_key = 2;
rcalpha = 0.05;
kover = 8;
vbias_rel = 0.5;
u_pi = 3.2;
vbias = -vbias_rel*u_pi;
laser_wavelength = 1310;
laser_linewidth = 1e6;
% Channel
link_length = 0;
vnle_order1 = 50;
vnle_order2 = 0;
vnle_order3 = 0;
vnle_order=[vnle_order1,vnle_order2,vnle_order3];
dfe_order = [0 0 0];
alpha = 0;
len_tr = 4096*2;
mu_ffe1 = 0.0001;
mu_ffe2 = 0.0008;
mu_ffe3 = 0.001;
mu_dc = 0.005;
% mu_dc = 0;
mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
mu_dfe = 0.0004;
dfe_ = sum(dfe_order)>0;
doub_mode = db_mode.no_db;
cols = linspecer(6);
rop = [-8];
bwl = [0.5:0.1:1.5];
fsym = [208:16:256].*1e9;
nonlin_mod = [0.5:0.01:0.75];
fsym = ones(size(nonlin_mod)).*fsym(1);
ffe_results = {};
mlse_results_lin= {};
vnle_results= {};
mlse_results_nonlin= {};
mlse_results_nonlin_states= {};
g_eye = GifWriter('Name','eye','Parallel',true);
g_mod = GifWriter('Name','modulator','Parallel',true);
for r = 1:length(nonlin_mod)
Pform = Pulseformer("fsym",fsym(r),"fdac",4*fsym(r),"pulse","rc","pulselength",16,"alpha",rcalpha);
db_precode = 0;
db_encode = 0;
duob_mode = db_mode.no_db;
apply_pulsef = 1;
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
"fsym",fsym(r),"M",M,"order",19,"useprbs",0,...
"fs_out",fdac,...
"applyclipping",0,"clipfactor",1.5,...
"applypulseform",apply_pulsef,"pulseformer",Pform,...
"randkey",random_key,...
"db_precode",db_precode,"db_encode",db_encode,...
"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
% 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);
El_sig = M8199B("kover",kover).process(Digi_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);
%%%%% Low-pass el. components %%%%%%
% tx_bwl = 100e9;
% El_sig = Filter('filtdegree',3,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
%%%%% Electrical Driver Amplifier %%%%%%
El_sig = El_sig.normalize("mode","oneone");
% El_sig = El_sig.setPower(1,"dBm");
% figure;histogram(El_sig.signal);
%%%%% MODULATE E/O CONVERSION %%%%%
u_pi = 3.2;
vbias = -u_pi*nonlin_mod(r);
[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);
if 1
figure(15);
hold on
scatter(El_sig.signal(1:100000)+vbias,(abs(Opt_sig.signal(1:100000)).^2)*1e3,0.1,'.','DisplayName','Modulator TF')
xlabel('Input in V')
ylabel('abs(Eopt)2 in mW','Interpreter','latex')
ylim([0 2]);
xlim([-3.2 0]);
g_mod.addFrame(15, r);
Opt_sig.eye(fsym(r), M, "fignum", 103837);
g_eye.addFrame(103837, r);
end
%%%%%% Fiber %%%%%%
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);
%%%%%% ROP %%%%%%
Opt_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
%%%%%% PD Square Law %%%%%%
PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",random_key).process(Opt_sig);
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
rx_bwl = 70e9;
PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig);
% %%%%%% Low-pass Scope %%%%%%
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
%%%%%% Scope %%%%%%
Scpe_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(PD_sig);
Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym(r));
% Scpe_sig_resampled.signal = Scpe_sig_resampled.signal(1:2*length(Symbols));
[~, Scpe_cell, ~, found_sync] = Scpe_sig_2sps.tsynch("reference", Symbols, "fs_ref", fsym(r), "debug_plots", 0);
Rx_sig = Scpe_cell{1};
Rx_sig = Rx_sig.normalize("mode","rms");
if 1
%% FFE
% ffe_order = [50, 0, 0];
% 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);
%
% ffe_results = ffe(eq_ffe,M,Rx_sig,Symbols,Tx_bits,...
% "precode_mode",duob_mode,...
% 'showAnalysis',0,...
% "postFFE",[],...
% "eth_style_symbol_mapping",0);
%
% ffe_results.metrics.print;
% ffe_results.config.equalizer_structure = "ffe";
%
%% MLSE linear
pf_ncoeffs = 1;
ffe_order = [50, 0, 0];
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);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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);
[ffe_results{r}, mlse_results_lin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
"precode_mode", duob_mode,...
'showAnalysis', 0, ...
"postFFE", [],...
"eth_style_symbol_mapping", 0);
mlse_results_lin{r}.metrics.print;
ffe_results{r}.metrics.print;
%% MLSE nonlinear pre
pf_ncoeffs = 1;
ffe_order = [50, 1, 0];
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);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',0,'trellis_state_mode',2);
[vnle_results{r}, mlse_results_nonlin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
"precode_mode", duob_mode,...
'showAnalysis', 0, ...
"postFFE", [],...
"eth_style_symbol_mapping", 0);
mlse_results_nonlin{r}.metrics.print;
vnle_results{r}.metrics.print;
%% nonlinear states MLSE linear pre
pf_ncoeffs = 1;
ffe_order = [50, 0, 0];
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);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',0,'trellis_state_mode',3);
[~, mlse_results_nonlin_states{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig, Symbols, Tx_bits, ...
"precode_mode", duob_mode,...
'showAnalysis', 0, ...
"postFFE", [],...
"eth_style_symbol_mapping", 0);
mlse_results_nonlin_states{r}.metrics.print;
end
end
g_mod.compile(15);
g_eye.compile(103837);
%%
figure();hold on;
plot(nonlin_mod,cellfun(@(x) x.metrics.BER, ffe_results),'DisplayName','FFE')
plot(nonlin_mod,cellfun(@(x) x.metrics.BER, vnle_results),'DisplayName','VNLE')
plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_lin),'DisplayName','FFE+MLSE')
plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_nonlin_states),'DisplayName','FFE+nonlin. states MLSE')
plot(nonlin_mod,cellfun(@(x) x.metrics.BER, mlse_results_nonlin),'DisplayName','VNLE+MLSE')
xlabel('Nonlinear Driving');
ylabel('BER')
set(gca,'YScale','log');
legend;
ylim([1e-4 1e-1]);
beautifyBERplot;