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new plots for Diss. Mostly AI gen. Few changes in actual codebase

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This commit is contained in:
Silas Oettinghaus
2026-07-30 08:35:45 +02:00
parent 125d8508ca
commit 7a9deaeb0c
62 changed files with 6171 additions and 630 deletions
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23
Functions/EQ_blocks/duobinary_target.m
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@@ -104,13 +104,13 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
[bits_db,errors_db,ber_db,a] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
burst_db = count_error_bursts(a, 40);
cols = linspecer(8);
figure();hold on;
stem(1:40,burst_db,'LineWidth',1,'Color',cols(4,:),'Marker','_','DisplayName','w/o diff. precoder');
stem(1:40,burst_db_precoded,'LineWidth',1,'Color',cols(3,:),'Marker','.','LineStyle','-','DisplayName','w diff. precoder');
xlabel('Bit Error Burst Length')
ylabel('Occurence')
set(gca, 'yscale', 'log');
% cols = linspecer(8);
% figure();hold on;
% stem(1:40,burst_db,'LineWidth',1,'Color',cols(4,:),'Marker','_','DisplayName','w/o diff. precoder');
% stem(1:40,burst_db_precoded,'LineWidth',1,'Color',cols(3,:),'Marker','.','LineStyle','-','DisplayName','w diff. precoder');
% xlabel('Bit Error Burst Length')
% ylabel('Occurence')
% set(gca, 'yscale', 'log');
end
% M = numel(unique(tx_symbols.signal));
@@ -118,6 +118,8 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
[bits_db,errors_db,ber_db,errorIndice_db] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
[snr_db_target, snr_db_target_lvl] = calc_snr(db_ref_sequence.signal, eq_noise.signal);
alpha = arburg(eq_noise.signal,1);%pf_.coefficients(2);
alpha = alpha(2);
@@ -152,6 +154,8 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
db_results.metrics.AIR = air_mlse;
db_results.metrics.MLSE_dir = mlse_.DIR;
db_results.metrics.Alpha = alpha;
db_results.metrics.SNR = snr_db_target;
db_results.metrics.SNR_level = snr_db_target_lvl;
% Create DB results structure
db_results.config = Equalizerstruct();
@@ -177,7 +181,10 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
showEQNoisePSD(eq_noise,"fignum",250,"displayname",'Duobinary Target Noise after Equalization');
fprintf('DB tgt BER: %.2e \n',ber_db);
if options.decoding_mode == db_decoder.sequencedetection
fprintf('DB tgt BER: %.2e \n',ber_db); %not relevant for memoryless, wont work
end
fprintf('DB tgt BER precoded: %.2e \n',ber_db_diff_precoded);
figure(341); clf;
tx_symbols_uncoded = Duobinary().decode(db_ref_sequence);

11
Functions/EQ_blocks/vnle_postfilter_mlse.m
View File

@@ -50,6 +50,11 @@ eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
[tx_symbols_pr,~] = pf_.process(tx_symbols, eq_noise);
% Calc SNR of Partial Response Signal
pr_noise = tx_symbols_pr-mlse_sig_sd;
[snr_partial_response, ~] = calc_snr(tx_symbols_pr.signal, pr_noise.signal);
if 0 %tx_symbols.fs > 190e9
if pf_.ncoeff == 1
if pf_.coefficients(2) < 0
@@ -83,7 +88,7 @@ mlse_sig_hd = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).qua
%% Calculate performance metrics
% VNLE metrics
[snr_vnle, snr_vnle_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
[snr_full_response, snr_vnle_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
% [gmi_vnle] = calc_air(eq_signal_sd, tx_symbols, "skip_front", 10000, "skip_end", 10000);
%calculate bitwise GMI
@@ -131,7 +136,7 @@ ffe_results.metrics.numBits = numbits.vnle;
ffe_results.metrics.numBitErr = errors.vnle;
ffe_results.metrics.BER_precoded = bers.vnle_precoded;
ffe_results.metrics.numBitErr_precoded = errors.vnle_precoded;
ffe_results.metrics.SNR = snr_vnle;
ffe_results.metrics.SNR = snr_full_response;
ffe_results.metrics.SNR_level = snr_vnle_lvl;
ffe_results.metrics.STD = std_vnle_total;
ffe_results.metrics.STD_level = std_vnle_lvl;
@@ -165,7 +170,7 @@ mlse_results.metrics.numBits = numbits.mlse;
mlse_results.metrics.numBitErr = errors.mlse;
mlse_results.metrics.BER_precoded = bers.mlse_precoded;
mlse_results.metrics.numBitErr_precoded = errors.mlse_precoded;
% mlse_results.metrics.SNR = NaN;
mlse_results.metrics.SNR = snr_partial_response;
mlse_results.metrics.GMI = gmi_mlse;
mlse_results.metrics.AIR = air_mlse;
% mlse_results.metrics.EVM = NaN;