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- Fixed 'ML_MLSE'

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- Added weighted DFE to 'EQ' (work in progress).
- Added the folders 'Evaluation Scripts' and 'Data' in 'projects\FSO_transmission', which contain different evaluations and measured data regarding the FSO transmission data.
This commit is contained in:
magf
2026-01-20 13:36:21 +01:00
parent 3b44315eea
commit 616945bf27
8 changed files with 635 additions and 52 deletions
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60
projects/ML_based_MLSE/theoretic_channel_evaluation.m
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@@ -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;