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ML_MLSE (before testing in depth)

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minor changes here and there
This commit is contained in:
Silas Oettinghaus
2025-10-31 10:36:13 +01:00
parent b27f1d3715
commit 09f345aa91
7 changed files with 583 additions and 158 deletions
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126
projects/ML_based_MLSE/model.m
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@@ -22,9 +22,9 @@ alpha = 0;
doub_mode = db_mode.no_db;
cols = linspecer(6);
rop = [-6];
rop = [-5];
bwl = [0.5:0.1:1.5];
fsym = [208:16:256].*1e9;
fsym = [212:16:256].*1e9;
% nonlin_mod = [0.5:0.01:0.75];
nonlin_mod = ones(size(fsym)).*0.5;
@@ -41,7 +41,7 @@ for r = 1:length(fsym)
apply_pulsef = 1;
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
"fsym",fsym(r),"M",M,"order",17,"useprbs",0,...
"fsym",fsym(r),"M",M,"order",18,"useprbs",0,...
"fs_out",fdac,...
"applyclipping",0,"clipfactor",1.5,...
"applypulseform",apply_pulsef,"pulseformer",Pform,...
@@ -94,59 +94,87 @@ for r = 1:length(fsym)
[~, 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");
showLevelHistogram(Rx_sig_1sps,Symbols,"displayname",'ffe','fignum',111);
%% Implement DSP directly here:
%%
mu_lms = 0.0005;
% 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",1);
% [Eq_signal,Vit_signal] = eq.process(Rx_sig_2sps,Symbols);
% toc
eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",2,"dd_mode",1,"adaption_technique","lms");
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
% FFE
[y_ffe, ffe_noise] = eq_.process(Rx_sig_2sps, Symbols);
Eq_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_ffe);
[~, errors, ber_ffe, ~] = calc_ber(Eq_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
fprintf('FFE: %.2e \n',ber_ffe);
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
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);
% Postfilter
[y_white,whitened_noise] = pf_.process(y_ffe, ffe_noise);
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);
% Sequence Est
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,'DIR',pf_.coefficients);
[y_mlse] = mlse_.process(y_white,Symbols);
Vit_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_mlse);
[~, errors, ber_mlse_normal, errpos] = calc_ber(Vit_bits.signal, Tx_bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('MLSE: %.2e \n',ber_mlse_normal);
showLevelHistogram(y_ffe,Symbols,"displayname",'ffe','fignum',111);
% showLevelHistogram(y_white,Symbols,"displayname",'ffe','fignum',111);
%% optimize length
mu_lms = 0.15;
eq = ML_MLSE("epochs_tr",5,"epochs_dd",5,"len_tr",2^14,...
"mu_dd",mu_lms,"mu_tr",mu_lms,"order",5,"sps",2,...
"traceback_depth",128,"L",2,"delta",0);
[y_ml_mlse,Vit_signal] = eq.process(Rx_sig_2sps,Symbols);
y_ml_mlse_ = y_ml_mlse;
y_ml_mlse_.signal = circshift(y_ml_mlse.signal,0);
Vit_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_ml_mlse_);
[~, errors, ber, errpos] = calc_ber(Vit_bits.signal, Tx_bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('ML MLSE: %.2e \n',ber);
bursts = count_error_bursts(errpos, 10);
e = zeros(size(Vit_bits.signal));
e(errpos) = 1;
figure(8)
stem(e)
%% optimize delta
deltas = [-1:4];
ber = zeros(1,length(deltas));
parfor m = 1:numel(deltas)
mu_lms = 0.2;
eq = ML_MLSE("epochs_tr",2,"epochs_dd",5,"len_tr",2^13,...
"mu_dd",mu_lms,"mu_tr",mu_lms,"order",4,"sps",1,...
"traceback_depth",128,"L",3,"delta",deltas(m));
[y_ml_mlse,Vit_signal] = eq.process(y_ffe,Symbols);
y_ml_mlse_ = y_ml_mlse;
y_ml_mlse_.signal = circshift(y_ml_mlse.signal,0);
Vit_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_ml_mlse_);
[~, errors, ber(m), errpos] = calc_ber(Vit_bits.signal, Tx_bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
fprintf('ML MLSE: %.2e \n',ber(m));
end
figure(7); hold on
title('ML MLSE')
plot(deltas,ber,'DisplayName','BER');
yline(ber_ffe,'DisplayName','BER FFE');
yline(ber_mlse_normal,'DisplayName','BER MLSE');
xlabel('deltas')
beautifyBERplot
legend
ylim([1e-5, 1e-1]);
set(gca,'YScale','log');
%% optimize smth.
tr_len = 2.^[2:15];
tr_len = floor(tr_len);
ber = zeros(size(tr_len));
for 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
@@ -163,12 +191,12 @@ for r = 1:length(fsym)
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_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",50,"sps",2,"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, ...
[ffe_results{r}, mlse_results_lin{r}] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Rx_sig_2sps, Symbols, Tx_bits, ...
"precode_mode", duob_mode,...
'showAnalysis', 0, ...
"postFFE", [],...