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Revert "Merge branch 'main' of https://cau-git.rz.uni-kiel.de/nt/mitarbeiter/silas/imdd_simulation"

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This reverts commit 798a0ca3b3
This commit is contained in:
Magnus Fischer
2026-02-02 12:12:33 +00:00
parent 005e821131
commit 9093fb2452
31 changed files with 385 additions and 2067 deletions
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16
projects/ML_based_MLSE/analyze_filter_length.m
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@@ -5,9 +5,9 @@ M = 4;
randkey = 1;
% --- Parameter sweep
order_range = 5:5:50; % FFE order
delta_range = 0:5:20; % delta
SNR_dB = 30;
order_range = 2:3:11; % FFE order
delta_range = 0:2:4; % delta
SNR_dB = 20;
% --- Prepare bit sequence
order_bits = 19;
@@ -21,14 +21,10 @@ Symbols = PAMmapper(M,0).map(Bits);
Symbols.fs = 200e9;
% --- Channel (minimal ISI + AWGN)
h = abs([0.3 0.9 0.3]); h = h/norm(h);
% h = [1 -1.67085330039878 1.17918163282514 -0.805210559745616 0.571564213123367 -0.296337147529674 0.00649773445209780 0.0854177610195952 -0.0576009020965258 0.0520994427061551 -0.0624586034913656 0.0553280962699552 -0.00705582559925755 -0.0336399056707792 0.0706903719452810 -0.0334124287931977 0.0131699455037966 0.0587431373842994 -0.0515902976066452 0.00647904355473619 0.0137506750904990 -0.0547974515885928 0.00994735499340592 -0.0135513582534086 -0.00463322575007739 0.0277311946101940];
% h = h/norm(h);
h = [0.3 0.9 0.3]; h = h/norm(h);
symbols_filt = Symbols.filter(h,1);
symbols_noi = symbols_filt;
symbols_noi.signal = awgn(symbols_filt.signal,SNR_dB,'measured');
symbols_noi.spectrum();
% --- Generate all parameter pairs
[O,D] = ndgrid(order_range, delta_range);
@@ -42,7 +38,7 @@ ce_vec = nan(size(pairs,1),1);
ce_training = nan(size(pairs,1),training_len);
% --- Parallel loop over parameter pairs
for k = 1:size(pairs,1)
parfor k = 1:size(pairs,1)
order_k = pairs(k,1);
delta_k = pairs(k,2);
@@ -93,7 +89,7 @@ end
beautifyBERplot
ylabel('BER'); xlabel('Filter Order [N]');
title('BER vs. Filter order');
% ylim([1e-4, 0.1]);
ylim([1e-4, 0.1]);
yline(3.8e-3,'HandleVisibility','off');
yline(2.2e-4,'HandleVisibility','off');

60
projects/ML_based_MLSE/theoretic_channel_evaluation.m
View File

@@ -48,36 +48,36 @@ for i = 1:numel(SNR_dB)
symbols_noi = symbols_filt;
symbols_noi.signal = awgn(symbols_filt.signal, SNR_dB(i), 'measured'); % AWGN with given SNR
% Sequence Est L=5
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',h);
mlse_.DIR = h;
[y_mlse] = mlse_.process(symbols_noi,Symbols);
mlse_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_mlse);
[~, ~, ber_mlse_l5(i), ~] = calc_ber(mlse_bits.signal, Bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('MLSE L5: %.2e \n',ber_mlse_l5(i));
% 2nd Approach
mu_lms = 0.0005;
pf_ncoeffs = 1;
eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",16,"sps",1,"dd_mode",1,"adaption_technique","lms");
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
% FFE
[y_ffe, ffe_noise] = eq_.process(symbols_noi, Symbols);
Eq_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_ffe);
[~, ~, ber_ffe(i), ~] = calc_ber(Eq_bits.signal, Bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
fprintf('FFE: %.2e \n',ber_ffe(i));
% Postfilter
[y_white,~] = pf_.process(y_ffe, ffe_noise);
% 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);
mlse_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_mlse);
[~, errors, ber_nwf_mlse_l2(i), errpos] = calc_ber(mlse_bits.signal, Bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('MLSE: %.2e \n',ber_nwf_mlse_l2(i));
% % Sequence Est L=5
% 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',h);
% mlse_.DIR = h;
% [y_mlse] = mlse_.process(symbols_noi,Symbols);
% mlse_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_mlse);
% [~, ~, ber_mlse_l5(i), ~] = calc_ber(mlse_bits.signal, Bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
% fprintf('MLSE L5: %.2e \n',ber_mlse_l5(i));
%
% % 2nd Approach
% mu_lms = 0.0005;
% pf_ncoeffs = 1;
% eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",2^13,"mu_dd",mu_lms,"mu_tr",mu_lms,"order",16,"sps",1,"dd_mode",1,"adaption_technique","lms");
% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
%
% % FFE
% [y_ffe, ffe_noise] = eq_.process(symbols_noi, Symbols);
%
% Eq_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_ffe);
% [~, ~, ber_ffe(i), ~] = calc_ber(Eq_bits.signal, Bits.signal, "skip_front", 0, "skip_end", 0, "returnErrorLocation", 1);
% fprintf('FFE: %.2e \n',ber_ffe(i));
%
% % Postfilter
% [y_white,~] = pf_.process(y_ffe, ffe_noise);
%
% % 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);
% mlse_bits = PAMmapper(M, 0, "eth_style", 0).demap(y_mlse);
% [~, errors, ber_nwf_mlse_l2(i), errpos] = calc_ber(mlse_bits.signal, Bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
% fprintf('MLSE: %.2e \n',ber_nwf_mlse_l2(i));
% ML-base MLSE L=2
adaptive_mu = 0;