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halfway merged and pulled?!

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Silas Labor Zizou
2025-12-15 15:41:02 +01:00
parent 7d0a634b87
commit b8cecae895
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316
Functions/EQ_structures/dsp_runid.m Normal file
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function [output] = dsp_runid(run_id, options)
arguments
run_id
options.append_to_db = 0;
options.max_occurences = 4;
options.parameters = struct();
options.database_type
options.dataBase
options.load_file_path = struct();
options.storage_path
options.mode
end
try
% Initialize output structures
output.ffe_package = {};
output.mlse_package = {};
output.vnle_package = {};
output.dbtgt_package = {};
output.dbenc_package = {};
output.mlmlse_package = {};
if options.mode == "load_run_id" || options.append_to_db
% Initialize database connection
database = DBHandler("dataBase", [options.dataBase], "type", options.database_type );
if 0
% 2. Check if an equalizer configuration with the same hash exists
queryStr = sprintf('SELECT COUNT(DISTINCT eq_id) AS unique_eq_count, COUNT(*) AS entries_for_run FROM `Results` WHERE run_id = %d', run_id);
existing_results = database.fetch(queryStr);
if existing_results.unique_eq_count >= 6
if (existing_results.entries_for_run / existing_results.unique_eq_count) > 5
return
end
end
end
end
if options.mode == "load_run_id"
dataTable = queryRunid(run_id, database);
fsym = dataTable.symbolrate;
M = double(dataTable.pam_level);
duob_mode = db_mode(strrep(dataTable.db_mode,'"',''));
% if database.checkIfRunExists('Results','run_id',run_id)
% disp(['Already got at least one reulst for run id: ',num2str(run_id),' '])
% return
% end
% Load and Sync signal data from DB
[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncSignalDataFromDb(dataTable, options);
elseif options.mode == "load_files"
Tx_bits = load(options.load_file_path.tx_bits_path);
Symbols = load(options.load_file_path.tx_symbols_path);
Scpe_sig_raw = load(options.load_file_path.rx_raw_path);
Tx_bits = Tx_bits.Bits;
Symbols = Symbols.Symbols;
Scpe_sig_raw = Scpe_sig_raw.Scpe_sig_raw;
fsym = Symbols.fs;
M = Symbols.logbook.ModifierCopy{1}.M;
duob_mode = Symbols.logbook.ModifierCopy{1}.duobinary_mode;
Scpe_sig_resampled = Scpe_sig_raw.resample("fs_in", Scpe_sig_raw.fs, "fs_out", 2*fsym);
[~, Scpe_cell, ~, found_sync] = Scpe_sig_resampled.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
else
% Run quick Simulation
tx_simulation;
end
% Handle Settings and argument replacement
len_tr = 4096*2;
ffe_order = [50, 5, 5];
dfe_order = [0, 0, 0];
pf_ncoeffs = 1;
mu_ffe = [0.0001, 0.0008, 0.001];
mu_dfe = 0.0004;
mu_dc = 0.005;
dc_buffer_len = 1;
mu_tr = 0;
mu_dd = 0.05;
adaption= 1;
use_dd_mode = 1;
use_ffe = 0;
use_dfe = 0;
use_vnle_mlse = 0;
use_dbtgt = 0;
use_dbenc = 0;
use_ml_mlse = 1;
addProcessingResultToDatabase = 0;
% Overwrite default parameters if given in options.parameters
paramStruct = options.parameters;
if ~isempty(paramStruct)
paramNames = fieldnames(paramStruct);
for i = 1:numel(paramNames)
thisName = paramNames{i};
thisValue = paramStruct.(thisName);
eval([thisName ' = thisValue;']);
end
end
% Configure equalizers
options.max_occurences = min(options.max_occurences,length(Scpe_cell));
for r = 1:options.max_occurences
%FFE
% eq_dfe = FFE("epochs_tr",5,"epochs_dd",2,"len_tr",2^13,"mu_dd",mu_dd,"mu_tr",mu_tr,"order",25,"sps",2,"decide",0, "adaption",adaption_method(adaption),"dd_mode",use_dd_mode);
%
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
% mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
eq_post = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0,"adaption_technique","lms");
eq_post = FFE("epochs_tr",5,"epochs_dd",2,"len_tr",2^13,"mu_dd",mu_dd,"mu_tr",mu_tr,"order",25,"sps",2,"decide",0, "adaption",adaption_method(adaption),"dd_mode",use_dd_mode);
% Duobinary signaling (db encoded)
mlse_db_enc = MLSE("DIR", [1,1], "duobinary_output", 0, "M", M, "trellis_states", PAMmapper(M,0).levels);
eq_db_enc = EQ("Ne", ffe_order, "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);
% Preprocess signal
Scpe_sig = preprocessSignal(Scpe_cell{r}, Symbols, fsym);
Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',-6);
Scpe_sig.spectrum("fignum",201,"normalizeTo0dB",0,"displayname",'Rx');
ylim([-30,3]);
xlim([-5,100]);
% Scpe_sig.spectrum("fignum",22233,"normalizeTo0dB",0,"displayname",'Rx');
% Scpe_sig.eye(fsym,M,"fignum",1024);
if duob_mode ~= db_mode.db_encoded
if use_ffe
ffe_order = [50, 0, 0];
eq_dfe = 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_dfe,M,Scpe_sig,Symbols,Tx_bits,...
"precode_mode",duob_mode,...
'showAnalysis',0,...
"postFFE",[],...
"eth_style_symbol_mapping",0);
output.ffe_package{r} = ffe_results;
ffe_results.metrics.print;
ffe_results.config.equalizer_structure = "ffe";
if options.append_to_db
database.addProcessingResult(run_id, ffe_results.metrics, ffe_results.config);
end
end
if use_dfe
ffe_order = [50, 5, 5];
eq_dfe = EQ("Ne",ffe_order,"Nb",[2,0,0],"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);
dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits,...
"precode_mode",duob_mode,...
'showAnalysis',0,...
"postFFE",[],...
"eth_style_symbol_mapping",0);
output.ffe_package{r} = dfe_results;
dfe_results.config.equalizer_structure = "dfe";
dfe_results.metrics.print;
if options.append_to_db
database.addProcessingResult(run_id, dfe_results.metrics, dfe_results.config);
end
end
if use_vnle_mlse
pf_ncoeffs = 1;
ffe_order = [50, 5, 5];
eq_ = EQ("Ne",ffe_order,"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",0);
% eq_ = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0.0004,"order",[50,5,5],"sps",2,"decide",0);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
useviterbi = 0;
if useviterbi
mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
else
if duob_mode == db_mode.no_db && M == 6 %only for PAM-6 and no duobinary precoding, otherwise leads to false sequence estimation
trellexlusion = 1;
else
trellexlusion = 0;
end
%state_mode 3 -> stat lvl; state_mode 2 -> use target lvls
%scale_mode 2 -> mmse adaption
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',trellexlusion,'trellis_state_mode',2);
end
[ffe_results, mlse_results] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Scpe_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 = "vnle";
mlse_results.metrics.print;
output.mlse_package{r} = mlse_results;
output.vnle_package{r} = ffe_results;
if options.append_to_db
database.addProcessingResult(run_id, mlse_results.metrics, mlse_results.config);
database.addProcessingResult(run_id, ffe_results.metrics, ffe_results.config);
end
end
if use_ml_mlse
%ML-based MLSE (L=2)
mu_ml = 0.01; training_epochs = 100;
ml_mlse_equalizer = ML_MLSE("epochs_tr",training_epochs,"epochs_dd",1, ...
"len_tr",length(Scpe_sig),"mu_dd",mu_ml,"mu_tr",mu_ml,"order",11,"sps",2, ...
"traceback_depth",128,"L",1,"delta",4,"adaptive_mu",0);
[ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Scpe_sig, Symbols, Tx_bits,"precode_mode",duob_mode);
output.mlmlse_package{r} = ml_mlse_results;
if options.append_to_db
database.addProcessingResult(run_id, ml_mlse_results.metrics, ml_mlse_results.config);
end
end
if use_dbtgt
useviterbi = 0;
if useviterbi
mlse_db_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
else
if duob_mode == db_mode.no_db && M == 6 %only for PAM-6 and no duobinary precoding, otherwise leads to false sequence estimation
trellexlusion = 1;
else
trellexlusion = 0;
end
mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',trellexlusion,'trellis_state_mode',3);
end
ffe_order = [50, 5, 5];
eq_ = EQ("Ne",ffe_order,"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);
dbt_results = duobinary_target(eq_, mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
"precode_mode", duob_mode, ...
'showAnalysis', 0,...
"postFFE", []);
dbt_results.metrics.print;
output.dbtgt_package{r} = dbt_results;
if options.append_to_db
database.addProcessingResult(run_id, dbt_results.metrics, dbt_results.config);
end
end
end
if duob_mode == db_mode.db_encoded
mlse_db_enc = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
mlse_db_enc = MLSE("DIR", [1,1], "duobinary_output", 0, "M", M, "trellis_states", PAMmapper(M,0).levels);
db_results = duobinary_signaling(eq_db_enc, mlse_db_enc, M, Scpe_sig, Symbols, Tx_bits, "precode_mode",duob_mode, "showAnalysis",0,"postFFE",[]);
output.dbenc_package{r} = db_results;
if options.append_to_db
database.addProcessingResult(run_id, db_results.metrics, db_results.config);
end
end
end
catch ME
save('workerError.mat','ME');
rethrow(ME);
end
end

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Functions/EQ_structures/ffe.m Normal file
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function [ffe_results] = ffe(eq_, M, rx_signal, tx_symbols, tx_bits, options)
% FFE Processes signals through FFE equalizer
%
% Inputs:
% eq_ - Equalizer object
% M - Modulation order
% rx_signal - Received signal
% tx_symbols - Transmitted symbols
% tx_bits - Transmitted bits
% options - Optional parameters
%
% Outputs:
% ffe_results - Results from FFE processing
arguments
eq_
M
rx_signal
tx_symbols
tx_bits
options.precode_mode db_mode
options.showAnalysis = 0;
options.eth_style_symbol_mapping = 0;
options.postFFE = [];
options.database = [];
end
%% Process signals through equalizer
% FFE or VNLE
[eq_signal_sd, eq_noise] = eq_.process(rx_signal, tx_symbols);
% Apply post-FFE if provided
if ~isempty(options.postFFE)
tic
[eq_signal_sd, eq_noise] = options.postFFE.process(eq_signal_sd, tx_symbols);
toc
end
try
ch_coefficients = arburg(eq_noise.signal,1);
channel_alpha = ch_coefficients(2);
end
% Hard decision on FFE output
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
%% Calculate BER based on precoding mode
[bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, options.precode_mode, M, options.eth_style_symbol_mapping);
%% Calculate performance metrics
[snr, snr_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
% [gmi] = calc_air(eq_signal_sd, tx_symbols, "skip_front", 10000, "skip_end", 10000);
[gmi] = calc_ngmi(eq_signal_sd,tx_symbols);
gmi = max(gmi,0);
air = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi ./ log2(double(M));
[evm_total, evm_lvl] = calc_evm(eq_signal_sd, tx_symbols);
[std_total, std_lvl] = calc_std(eq_signal_sd, tx_symbols);
[std_rxraw_total, std_rxraw_lvl] = calc_std(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols);
%% Display analysis if requested
if options.showAnalysis
displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, tx_symbols, M, options.postFFE);
end
%% Prepare output structure
% Determine postFFE order
if ~isempty(options.postFFE)
npostFFE = options.postFFE.order;
else
npostFFE = 0;
end
% Create FFE results structure
ffe_results = struct();
try
eq_.e = [];
eq_.e2 = [];
eq_.e3 = [];
eq_.b = [];
eq_.b2 = [];
eq_.b3 = [];
end
ffe_results.config = Equalizerstruct();
ffe_results.config.eq = jsonencode(eq_);
ffe_results.config.equalizer_structure = int32(equalizer_structure.ffe);
ffe_results.config.comment = 'function: ffe';
ffe_results.metrics = Metricstruct;
ffe_results.metrics.result_id = NaN;
ffe_results.metrics.run_id = NaN;
ffe_results.metrics.eqParam_id = NaN;
ffe_results.metrics.date_of_processing = datetime('now');
ffe_results.metrics.BER = ber;
ffe_results.metrics.numBits = bits;
ffe_results.metrics.numBitErr = errors;
ffe_results.metrics.BER_precoded = ber_precoded;
ffe_results.metrics.numBitErr_precoded = errors_precoded;
ffe_results.metrics.SNR = snr;
ffe_results.metrics.SNR_level = snr_lvl;
ffe_results.metrics.STD = std_total;
ffe_results.metrics.STD_level = std_lvl;
ffe_results.metrics.STDrx = std_rxraw_total;
ffe_results.metrics.STDrx_level = std_rxraw_lvl;
ffe_results.metrics.GMI = gmi;
ffe_results.metrics.AIR = air;
ffe_results.metrics.EVM = evm_total;
ffe_results.metrics.EVM_level = evm_lvl;
ffe_results.metrics.Alpha = channel_alpha;
end
%% Helper Functions
function [bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, precode_mode, M, eth_style)
% Calculate BER based on precoding mode
mapper = PAMmapper(M, 0, "eth_style", eth_style);
switch precode_mode
case db_mode.no_db
% TX Data is not precoded
% A) Emulate diff precoding
eq_signal_hd_precoded = Duobinary().encode(eq_signal_hd, "M", M);
eq_signal_hd_precoded = Duobinary().decode(eq_signal_hd_precoded, "M", M);
tx_symbols_precoded = Duobinary().encode(tx_symbols);
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
tx_bits_precoded = mapper.demap(tx_symbols_precoded);
rx_bits = mapper.demap(eq_signal_hd_precoded);
[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
% B) Just determine BER
rx_bits = mapper.demap(eq_signal_hd);
[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
case db_mode.db_precoded
% Data is precoded on TX side
% A) Decode at Rx if no DB targeting was applied
eq_signal_hd_decoded = Duobinary().encode(eq_signal_hd, "M", M);
eq_signal_hd_decoded = Duobinary().decode(eq_signal_hd_decoded, "M", M);
rx_bits_decoded = mapper.demap(eq_signal_hd_decoded);
[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits_decoded.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
% B) Omit the Coding by comparing with demapped TX symbol sequence
tx_bits_demapped = mapper.demap(tx_symbols);
rx_bits = mapper.demap(eq_signal_hd);
[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits_demapped.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
end
end
function displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, tx_symbols, M, postFFE)
% Display analysis plots and metrics
% Initialize figure handles
% Corrected line - added tx_symbols as second positional argument
showLevelScatter(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols, "fignum", 100);
warning off
showLevelScatter(eq_signal_sd, tx_symbols, "fignum", 101);
figure(gcf);hold on; plot(((1:length(eq_noise.signal)) / eq_noise.fs) * 1e6,movmean(eq_noise.signal,2000,1), 'LineWidth',3,'Color','black')
warning on
showLevelHistogram(eq_signal_sd, tx_symbols, "fignum", 102);
showEQNoisePSD(eq_noise, "fignum", 103, "displayname", 'Residual Noise after FFE');
% Figure 2: Post-FFE coefficients (if available)
if ~isempty(postFFE)
showEQcoefficients('n1', postFFE.e, "displayname", 'Coefficients', 'fignum', 104);
end
try
figure(339);
showEQfilter(eq_.e_tr, eq_signal_sd.fs.*2,"displayname",'training','fignum',339);
showEQfilter(eq_.e, eq_signal_sd.fs.*2,"displayname",'dec. directed','fignum',339);
legend on
end
try
figure(240); hold on; plot(pow2db(movmean(eq_.debug_struct.error_tr',100)));ylim([-30,3]);title('error training');
figure(241); hold on; plot(pow2db(movmean(eq_.debug_struct.update_tr',100)));title('update step training');
figure(242); hold on; plot(pow2db(movmean(eq_.debug_struct.update',1000)));title('update step dd');
end
% eq_signal_sd.eye(eq_signal_sd.fs,M,"displayname",'Eye','fignum',105);
end

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function [ml_mlse_results] = ml_mlse(eq_, M, rx_signal, tx_symbols, tx_bits, options)
%
%
% Inputs:
% eq_ - Equalizer object
% M - Modulation order
% rx_signal - Received signal
% tx_symbols - Transmitted symbols
% tx_bits - Transmitted bits
% options - Optional parameters
%
% Outputs:
% ffe_results - Results from FFE processing
arguments
eq_
M
rx_signal
tx_symbols
tx_bits
options.precode_mode db_mode
options.eth_style_symbol_mapping = 0;
options.postFFE = [];
end
%% Process signals through equalizer
[eq_signal_hd,y_ref] = eq_.process(rx_signal,tx_symbols);
%% Calculate BER based on precoding mode
[bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, options.precode_mode, M, options.eth_style_symbol_mapping);
% Create FFE results structure
ml_mlse_results = struct();
try
eq_.e = [];
eq_.e2 = [];
eq_.e3 = [];
eq_.b = [];
eq_.b2 = [];
eq_.b3 = [];
end
ml_mlse_results.config = Equalizerstruct();
eq_small = strip_eq(eq_, 10);
json_str = jsonencode(eq_small);
ml_mlse_results.config.eq = jsonencode(eq_);
ml_mlse_results.config.equalizer_structure = int32(equalizer_structure.ml_mlse);
ml_mlse_results.config.comment = 'function: ML-based MLSE';
ml_mlse_results.metrics = Metricstruct;
% ml_mlse_results.metrics.result_id = NaN;
% ml_mlse_results.metrics.run_id = NaN;
% ml_mlse_results.metrics.eqParam_id = NaN;
ml_mlse_results.metrics.date_of_processing = datetime('now');
ml_mlse_results.metrics.BER = ber;
ml_mlse_results.metrics.numBits = bits;
ml_mlse_results.metrics.numBitErr = errors;
ml_mlse_results.metrics.BER_precoded = ber_precoded;
ml_mlse_results.metrics.numBitErr_precoded = errors_precoded;
% ml_mlse_results.metrics.SNR = NaN;
% ml_mlse_results.metrics.SNR_level = NaN;
% ml_mlse_results.metrics.STD = NaN;
% ml_mlse_results.metrics.STD_level = NaN;
% ml_mlse_results.metrics.STDrx = NaN;
% ml_mlse_results.metrics.STDrx_level = NaN;
% ml_mlse_results.metrics.GMI = NaN;
% ml_mlse_results.metrics.AIR = NaN;
% ml_mlse_results.metrics.EVM = NaN;
% ml_mlse_results.metrics.EVM_level = NaN;
% ml_mlse_results.metrics.Alpha = NaN;
end
%% Helper Functions
function [bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, precode_mode, M, eth_style)
% Calculate BER based on precoding mode
mapper = PAMmapper(M, 0, "eth_style", eth_style);
switch precode_mode
case db_mode.no_db
% TX Data is not precoded
% A) Emulate diff precoding
eq_signal_hd_precoded = Duobinary().encode(eq_signal_hd, "M", M);
eq_signal_hd_precoded = Duobinary().decode(eq_signal_hd_precoded, "M", M);
tx_symbols_precoded = Duobinary().encode(tx_symbols);
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
tx_bits_precoded = mapper.demap(tx_symbols_precoded);
rx_bits = mapper.demap(eq_signal_hd_precoded);
[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
% B) Just determine BER
rx_bits = mapper.demap(eq_signal_hd);
[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
case db_mode.db_precoded
% Data is precoded on TX side
% A) Decode at Rx if no DB targeting was applied
eq_signal_hd_decoded = Duobinary().encode(eq_signal_hd, "M", M);
eq_signal_hd_decoded = Duobinary().decode(eq_signal_hd_decoded, "M", M);
rx_bits_decoded = mapper.demap(eq_signal_hd_decoded);
[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits_decoded.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
% B) Omit the Coding by comparing with demapped TX symbol sequence
tx_bits_demapped = mapper.demap(tx_symbols);
rx_bits = mapper.demap(eq_signal_hd);
[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits_demapped.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1);
end
end
function eq_out = strip_eq(eq_, max_elems)
% strip_eq removes all large fields from the ML_MLSE object
% eq_out = strip_eq(eq_, max_elems)
% max_elems ... maximum number of elements to keep (default = 10)
if nargin < 2
max_elems = 10; % default threshold
end
props = properties(eq_);
for i = 1:numel(props)
val = eq_.(props{i});
if ~isempty(val)
% Count total number of elements
if numel(val) > max_elems
eq_.(props{i}) = [];
end
end
end
eq_out = eq_;
end