silas/imdd_silas
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

More focus on Database analysis and direct DSP'ing of run_id's

Browse Source
This commit is contained in:
Silas Oettinghaus
2025-04-08 10:21:41 +02:00
parent 74066d0669
commit e86930335e
20 changed files with 1008 additions and 187 deletions
Download Patch File Download Diff File Expand all files Collapse all files

100
Functions/EQ_structures/duobinary_signaling.m
View File

@@ -1,18 +1,96 @@
function [eq_package] = duobinary_signaling(eq_, mlse_,M ,rx_signal, tx_symbols, tx_bits)
%Duobinary Signaling
function [eq_package] = duobinary_signaling(eq_, mlse_,M ,rx_signal, tx_symbols, tx_bits,options)
%Duobinary Signaling
arguments
eq_
mlse_
M
rx_signal
tx_symbols
tx_bits
options.postFFE = [];
end
[eq_signal, eq_noise] = eq_.process(rx_signal,tx_symbols);
eq_signal = mlse_.process(eq_signal);
[eq_signal, eq_noise] = eq_.process(rx_signal,tx_symbols);
eq_signal = Duobinary().encode(eq_signal);
eq_signal = Duobinary().decode(eq_signal);
if ~isempty(options.postFFE)
[eq_signal,eq_noise] = options.postFFE.process(eq_signal,tx_symbols);
end
% M = numel(unique(eq_signal.signal));
rx_bits = PAMmapper(M,0).demap(eq_signal);
[~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
eq_signal = mlse_.process(eq_signal);
eq_signal = Duobinary().encode(eq_signal);
eq_signal = Duobinary().decode(eq_signal);
% M = numel(unique(eq_signal.signal));
rx_bits = PAMmapper(M,0).demap(eq_signal);
[bits_db,errors_db,ber_db,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
eq_package.ber = ber_db;
resultsDBsignaling = struct( ...
'result_id', NaN, ... %
'run_id', NaN, ... % Beispielhafte Run-ID
'eqParam_id', NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
'numBits', bits_db, ... % Beispiel: 1.000.000 Bits
'numBitErr', errors_db, ... % Beispiel: 120 Bitfehler
'BER_precoded', [], ... % BER = 120 / 1.000.000
'numBitErr_precoded', [], ... % Beispiel: 120 Bitfehler
'BER', ber_db, ... % BER = 120 / 1.000.000
'SNR', [], ... % Beispielhafte SNR
'SNR_level', jsonencode([]), ... % SNR-Level als JSON-codiertes Array
'GMI', [], ... % Beispielhafter GMI-Wert
'AIR', [], ... % Beispielhafter AIR-Wert
'EVM', [], ... % Beispielhafte EVM
'EVM_level', jsonencode([]), ... % EVM-Level als JSON-codiertes Array
'Alpha', [] ... % Beispielhafter Alpha-Wert
);
if ~isempty(options.postFFE)
npostFFE = options.postFFE.order;
else
npostFFE = 0;
end
equalizerConfigDBsignaling = struct( ...
'eq_id', NaN, ... % Auto-Inkrement, wird in der DB gesetzt
'equalizer_structure', int32(equalizer_structure.db_encoded), ... % Beispiel: 1 (z.B. für vnle)
'M', M, ... % Ordnung der PAM-Konstellation
'target_constellation', jsonencode(round(unique(tx_symbols.signal),5)), ... % Beispielhafter Target-String
'db_target', 1, ... % 0 oder 1
'diff_precode', 1, ... % 0 oder 1
'postFFE', ~isempty(options.postFFE), ... % Beispielwert
'NpostFFE', npostFFE, ... % Beispielwert
'Ne1', eq_.Ne(1), ... % Feedforward Koeffizienten 1. Ordnung
'Ne2', eq_.Ne(2), ... % Feedforward Koeffizienten 2. Ordnung
'Ne3', eq_.Ne(3), ... % Feedforward Koeffizienten 3. Ordnung
'Nb1', eq_.Nb(1), ... % Decision Feedback Koeffizienten 1. Ordnung
'Nb2', eq_.Nb(2), ... % Decision Feedback Koeffizienten 2. Ordnung
'Nb3', eq_.Nb(3), ... % Decision Feedback Koeffizienten 3. Ordnung
'K', eq_.K, ... % Samples pro Symbol
'DCmu', eq_.DCmu, ... % Anpassungsrate für DC-Tap
'ideal_dfe', eq_.ideal_dfe, ... % Flag für ideal DFE (0 oder 1)
'training_length', eq_.training_length, ... % Anzahl Trainingssymbole
'training_loops', eq_.training_loops, ... % Anzahl Trainingsdurchläufe
'TRmu1', eq_.FFEmu, ... % mu für DD-Modus (1. Ordnung)
'TRmu2', eq_.FFEmu, ... % mu für DD-Modus (2. Ordnung)
'TRmu3', eq_.FFEmu, ... % mu für DD-Modus (3. Ordnung)
'TRmuDFE', eq_.DFEmu, ... % mu für DFE-Modus im DD
'dd_loops', 5, ... % Anzahl Durchläufe im DD-Modus
'DDmu1', eq_.DDmu(1), ... % mu für DD-Modus (1. Ordnung)
'DDmu2', eq_.DDmu(2), ... % mu für DD-Modus (2. Ordnung)
'DDmu3', eq_.DDmu(3), ... % mu für DD-Modus (3. Ordnung)
'DDmuDFE', eq_.DDmu(4), ... % mu für DFE-Modus im DD
'MLSE_mode', 'viterbi', ... % Beispiel: MLSE-Modus als String
'MLSE_trellis_states', jsonencode(mlse_.trellis_states), ... % Trellis-States, z.B. als JSON-String oder kommasepariert
'comment', 'function: duobinary_target.m', ... % Zusätzliche Kommentare
'config_hash', NaN ...
);
eq_package.resultsDBsignaling = resultsDBsignaling;
eq_package.equalizerConfigDBsignaling = equalizerConfigDBsignaling;
eq_package.ber = ber;
end

45
Functions/EQ_structures/duobinary_target.m
View File

@@ -30,35 +30,42 @@ mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quanti
% precoding to mitigate error propagation, most prominently used in
% combination with duobinary signaling to avoid catastrophic error
% behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
% takes:
% -> eq_signal_hd: hard decision signal after eq
% -> tx_symbols: that where used as reference for eq
switch options.precode_mode
case db_mode.db_emulate
mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
case db_mode.no_db
% TX Data is not precoded:
% A) Emulate diff precoding
mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
tx_symbols_precoded = Duobinary().encode(tx_symbols);
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
tx_bits_precoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
case db_mode.db_discard
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_precoded);
[~,errors_db_diff_precoded,ber_db_diff_precoded,~] = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% normal dsp for precoded sequence == discard/omit/ignore precode
tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols);
case db_mode.db_encoded
% normal DB encoded data (only for 10KM)
%B) Just determine BER
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
[bits_mlse,errors_mlse,ber_db,~] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
case db_mode.db_precoded
mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
% Daten SIND TATSÄCHLICH precoded auf TX Seite:
% A) Decode at Rx if no DB targeting was applied (we are in VNLE or MLSE EQ structure here!
mlse_sig_hd_decoded = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd_decoded = Duobinary().decode(mlse_sig_hd_decoded,"M",M);
rx_bits_mlse_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_decoded);
[~,errors_db_diff_precoded,ber_db_diff_precoded,~] = calc_ber(rx_bits_mlse_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% B) Omit the Coding by comparing with demapped TX symbol sequence
tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols);
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
[bits_db,errors_db,ber_db,~] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
@@ -75,6 +82,8 @@ resultsDBtgt = struct( ...
'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
'numBits', bits_db, ... % Beispiel: 1.000.000 Bits
'numBitErr', errors_db, ... % Beispiel: 120 Bitfehler
'BER_precoded', ber_db_diff_precoded, ... % BER = 120 / 1.000.000
'numBitErr_precoded', errors_db_diff_precoded, ... % Beispiel: 120 Bitfehler
'BER', ber_db, ... % BER = 120 / 1.000.000
'SNR', [], ... % Beispielhafte SNR
'SNR_level', jsonencode([]), ... % SNR-Level als JSON-codiertes Array

245
Functions/EQ_structures/vnle_postfilter_mlse.m
View File

@@ -1,118 +1,128 @@
function [eq_package] = vnle_postfilter_mlse(eq_,pf_,mlse_,M,rx_signal,tx_symbols,tx_bits,options)
arguments
eq_
pf_
mlse_
M
rx_signal
tx_symbols
tx_bits
eq_
pf_
mlse_
M
rx_signal
tx_symbols
tx_bits
options.precode_mode db_mode
options.showAnalysis = 0;
options.eth_style_symbol_mapping = 0;
options.postFFE = [];
options.postFFE = [];
options.database = [];
end
%FFE or VNLE
[eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
%FFE or VNLE
[eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
if ~isempty(options.postFFE)
[eq_signal_sd,eq_noise] = options.postFFE.process(eq_signal_sd,tx_symbols);
end
if ~isempty(options.postFFE)
[eq_signal_sd,eq_noise] = options.postFFE.process(eq_signal_sd,tx_symbols);
end
eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
mlse_sig_sd = pf_.process(eq_signal_sd,eq_noise);
mlse_sig_sd = pf_.process(eq_signal_sd,eq_noise);
mlse_.DIR = pf_.coefficients;
% [mlse_sig_hd,mlse_sig_sd] = mlse_.process(mlse_sig_sd,tx_symbols);
mlse_sig_sd = mlse_.process(mlse_sig_sd);
mlse_.DIR = pf_.coefficients;
% [mlse_sig_hd,mlse_sig_sd] = mlse_.process(mlse_sig_sd,tx_symbols);
mlse_sig_sd = mlse_.process(mlse_sig_sd);
mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
% precoding to mitigate error propagation, most prominently used in
% combination with duobinary signaling to avoid catastrophic error
% behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
% precoding to mitigate error propagation, most prominently used in
% combination with duobinary signaling to avoid catastrophic error
% behavior (see J.W.M. Bergmans, Digital Baseband Transmission and Recording -> partial response signaling)
% takes:
% -> M
% -> eq_signal_hd: hard decision signal after eq
% -> tx_symbols: that where used as reference for eq
switch options.precode_mode
switch options.precode_mode
case db_mode.db_emulate
% re
eq_signal_hd = Duobinary().encode(eq_signal_hd,"M",M);
eq_signal_hd = Duobinary().decode(eq_signal_hd,"M",M);
case db_mode.no_db
% TX Data is not precoded:
mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
% 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);
mlse_sig_hd_precoded = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd_precoded = Duobinary().decode(mlse_sig_hd_precoded,"M",M);
tx_symbols_precoded = Duobinary().encode(tx_symbols);
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
tx_bits_precoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols_precoded);
case db_mode.db_discard
rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd_precoded);
[~,errors_vnle_diff_precoded,ber_vnle_diff_precoded,~] = calc_ber(rx_bits_vnle.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_precoded);
[~,errors_mlse_diff_precoded,ber_mlse_diff_precoded,~] = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
%B) Just determine BER
rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd);
[bits_vnle,errors_vnle,ber_vnle,~] = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
[bits_mlse,errors_mlse,ber_mlse,~] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
case db_mode.db_precoded
% Daten SIND TATSÄCHLICH precoded auf TX Seite:
% A) Decode at Rx if no DB targeting was applied (we are in VNLE or MLSE EQ structure here!
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_vnle_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd_decoded);
[~,errors_vnle_diff_precoded,ber_vnle_diff_precoded,~] = calc_ber(rx_bits_vnle_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
mlse_sig_hd_decoded = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd_decoded = Duobinary().decode(mlse_sig_hd_decoded,"M",M);
rx_bits_mlse_decoded = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd_decoded);
[~,errors_mlse_diff_precoded,ber_mlse_diff_precoded,~] = calc_ber(rx_bits_mlse_decoded.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% B) Omit the Coding by comparing with demapped TX symbol sequence
% normal dsp for precoded sequence == discard/omit/ignore precode
tx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(tx_symbols);
rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd);
[bits_vnle,errors_vnle,ber_vnle,~] = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
case db_mode.db_encoded
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
[bits_mlse,errors_mlse,ber_mlse,~] = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% normal DB encoded data (only for 10KM)
end
case db_mode.db_precoded
% METRICS OF VNLE SD Signal:
[snr_vnle,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);
air_vnle = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi_vnle ./ log2(double(M));
[evm_vnle_total,evm_vnle_lvl] = calc_evm(eq_signal_sd,tx_symbols);
eq_signal_hd = Duobinary().encode(eq_signal_hd,"M",M);
eq_signal_hd = Duobinary().decode(eq_signal_hd,"M",M);
% METRICS OF MLSE (HD-VITERBI)
pf_.ncoeff = 1;
pf_.process(eq_signal_sd,eq_noise);
alpha = pf_.coefficients(2);
mlse_sig_hd = Duobinary().encode(mlse_sig_hd,"M",M);
mlse_sig_hd = Duobinary().decode(mlse_sig_hd,"M",M);
eq_package.ber_mlse = ber_mlse;
eq_package.ber_vnle = ber_vnle;
eq_package.evm_vnle_total = evm_vnle_total;
eq_package.evm_vnle_lvl = evm_vnle_lvl;
eq_package.gmi = gmi_vnle;
end
eq_package.eq = eq_;
eq_package.pf = pf_;
eq_package.mlse = mlse_;
% METRICS OF VNLE %
rx_bits_vnle = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(eq_signal_hd);
[bits_vnle,errors_vnle,ber_vnle,errorIndice_vnle] = calc_ber(rx_bits_vnle.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
[snr_vnle,snr_vnle_lvl] = calc_snr(tx_symbols.signal,eq_noise.signal);
% correct TUM implementation of AIR
[gmi_vnle] = calc_air(eq_signal_sd,tx_symbols,"skip_front",10000,"skip_end",10000);
gmi_vnle = min(max(abs(gmi_vnle),0.1),0); %set to zero if no convergence of gmi below 0.1 to avoid negative or any other "dumb" value
air_vnle = tx_symbols.fs .* floor(log2(8)*10)/10 .* gmi_vnle;
[evm_vnle_total,evm_vnle_lvl] = calc_evm(eq_signal_sd,tx_symbols);
% METRICS OF MLSE (HD-VITERBI)
rx_bits_mlse = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
[bits_mlse,errors_mlse,ber_mlse,errorIndice_mlse]= calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
pf_.ncoeff = 1;
pf_.process(eq_signal_sd,eq_noise);
alpha = pf_.coefficients(2);
eq_package.ber_mlse = ber_mlse;
eq_package.ber_vnle = ber_vnle;
eq_package.evm_vnle_total = evm_vnle_total;
eq_package.evm_vnle_lvl = evm_vnle_lvl;
eq_package.gmi = gmi_vnle;
eq_package.eq = eq_;
eq_package.pf = pf_;
eq_package.mlse = mlse_;
resultsVNLE = struct( ...
resultsVNLE = struct( ...
'result_id', NaN, ... %
'run_id', NaN, ... % Beispielhafte Run-ID
'eqParam_id', NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
'BER', ber_vnle, ... % BER = 120 / 1.000.000
'numBits', bits_vnle, ... % Beispiel: 1.000.000 Bits
'numBitErr', errors_vnle, ... % Beispiel: 120 Bitfehler
'BER', ber_vnle, ... % BER = 120 / 1.000.000
'BER_precoded', ber_vnle_diff_precoded, ... % BER = 120 / 1.000.000
'numBitErr_precoded', errors_vnle_diff_precoded, ... % Beispiel: 120 Bitfehler
'SNR', snr_vnle, ... % Beispielhafte SNR
'SNR_level', jsonencode(snr_vnle_lvl), ... % SNR-Level als JSON-codiertes Array
'GMI', gmi_vnle, ... % Beispielhafter GMI-Wert
@@ -120,15 +130,15 @@ end
'EVM', evm_vnle_total, ... % Beispielhafte EVM
'EVM_level', jsonencode(evm_vnle_lvl), ... % EVM-Level als JSON-codiertes Array
'Alpha', [] ... % Beispielhafter Alpha-Wert
);
);
if ~isempty(options.postFFE)
npostFFE = options.postFFE.order;
else
npostFFE = 0;
end
if ~isempty(options.postFFE)
npostFFE = options.postFFE.order;
else
npostFFE = 0;
end
equalizerConfigVNLE = struct( ...
equalizerConfigVNLE = struct( ...
'eq_id', NaN, ... % Auto-Inkrement, wird in der DB gesetzt
'equalizer_structure', int32(equalizer_structure.vnle), ... % Beispiel: 1 (z.B. für vnle)
'M', M, ... % Ordnung der PAM-Konstellation
@@ -158,18 +168,20 @@ end
'DDmu3', eq_.DDmu(3), ... % mu für DD-Modus (3. Ordnung)
'DDmuDFE', eq_.DDmu(4), ... % mu für DFE-Modus im DD
'comment', 'function: vnle_postfilter_mlse', ... % Zusätzliche Kommentare
'config_hash', NaN ...
);
'config_hash', NaN ...
);
resultsMLSE = struct( ...
resultsMLSE = struct( ...
'result_id', NaN, ... %
'run_id', NaN, ... % Beispielhafte Run-ID
'eqParam_id', NaN, ... % Beispielhafter Fremdschlüssel zur EqualizerParameters-Tabelle
'date_of_processing', datetime('now'), ... % Aktuelles Datum und Uhrzeit
'BER', ber_mlse, ... % BER = 120 / 1.000.000
'numBits', bits_mlse, ... % Beispiel: 1.000.000 Bits
'numBitErr', errors_mlse, ... % Beispiel: 120 Bitfehler
'BER', ber_mlse, ... % BER = 120 / 1.000.000
'BER_precoded', ber_mlse_diff_precoded, ... % BER = 120 / 1.000.000
'numBitErr_precoded', errors_mlse_diff_precoded, ... % Beispiel: 120 Bitfehler
'SNR', [], ... % Beispielhafte SNR
'SNR_level', jsonencode([]), ... % SNR-Level als JSON-codiertes Array
'GMI', [], ... % Beispielhafter GMI-Wert
@@ -178,11 +190,10 @@ end
'EVM_level', jsonencode([]), ... % EVM-Level als JSON-codiertes Array
'Alpha', alpha, ... % Beispielhafter Alpha-Wert
'MLSE_dir', jsonencode([mlse_.DIR])...
);
);
equalizerConfigMLSE = struct( ...
equalizerConfigMLSE = struct( ...
'eq_id', NaN, ... % Auto-Inkrement, wird in der DB gesetzt
'equalizer_structure', int32(equalizer_structure.vnle_pf_mlse), ... % Beispiel: 1 (z.B. für vnle)
'M', M, ... % Ordnung der PAM-Konstellation
@@ -214,43 +225,43 @@ end
'MLSE_mode', 'viterbi', ... % Beispiel: MLSE-Modus als String
'MLSE_trellis_states', jsonencode(mlse_.trellis_states), ... % Trellis-States, z.B. als JSON-String oder kommasepariert
'comment', 'function: vnle_postfilter_mlse', ... % Zusätzliche Kommentare
'config_hash', NaN ...
);
eq_package.resultsVNLE = resultsVNLE;
eq_package.resultsMLSE = resultsMLSE;
eq_package.equalizerConfigVNLE = equalizerConfigVNLE;
eq_package.equalizerConfigMLSE = equalizerConfigMLSE;
'config_hash', NaN ...
);
eq_package.resultsVNLE = resultsVNLE;
eq_package.resultsMLSE = resultsMLSE;
eq_package.equalizerConfigVNLE = equalizerConfigVNLE;
eq_package.equalizerConfigMLSE = equalizerConfigMLSE;
% eq_package.vnle_out = eq_signal_sd;
if options.showAnalysis
% eq_package.vnle_out = eq_signal_sd;
if options.showAnalysis
% fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
% fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
fprintf('VNLE BER: %.2e \n',ber_vnle);
fprintf('VNLE BER: %.2e \n',ber_vnle);
fprintf('MLSE BER: %.2e \n',ber_mlse);
fprintf('MLSE BER: %.2e \n',ber_mlse);
showEQNoisePSD(eq_noise,"fignum",336,"displayname",'Residual Noise after VNLE','postfilter_taps',pf_.coefficients);
showEQNoisePSD(eq_noise,"fignum",336,"displayname",'Residual Noise after VNLE','postfilter_taps',pf_.coefficients);
rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
tx_symbols.spectrum("normalizeTo0dB",1,"fignum",337,'displayname','Tx Signal');
rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
showLevelHistogram(eq_signal_sd,tx_symbols)
% showLevelHistogram(mlse_sig_sd,tx_symbols)
tx_symbols.spectrum("normalizeTo0dB",1,"fignum",337,'displayname','Tx Signal');
showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients');
showLevelHistogram(eq_signal_sd,tx_symbols)
% showLevelHistogram(mlse_sig_sd,tx_symbols)
showEQNoiseSNR(tx_symbols,eq_noise,"displayname",'vnle snr','fignum',101);
showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients');
%%% EQ SNR Spectrum %230
%snr
showEQNoiseSNR(tx_symbols,eq_noise,"displayname",'vnle snr','fignum',101);
% showErrorBurstCount(eq_signal_sd,tx_symbols)
%%% EQ SNR Spectrum %230
%snr
end
% showErrorBurstCount(eq_signal_sd,tx_symbols)
end
end

62
Functions/Theory/modifiedGodardTimingRecovery.m Normal file
View File

@@ -0,0 +1,62 @@
function tau_error = modifiedGodardTimingRecovery(rx, N, eta, beta)
% modifiedGodardTimingRecovery
%
% This function estimates the symbol timing error using the modified Godard
% approach in the frequency domain as described in:
%
% "Modified Godard Timing Recovery for Non-Integer Oversampling Receivers"
% Appl. Sci. 2017, 7, 655. :contentReference[oaicite:0]{index=0}​:contentReference[oaicite:1]{index=1}
%
% Inputs:
% rx - Received time-domain signal (vector)
% N - FFT size (should be an even integer)
% eta - Effective oversampling factor used for timing recovery (eta > 1)
% beta - Roll-off related parameter (0 < beta <= 1)
%
% Output:
% tau_error - Estimated timing error (in sample units)
%
% Implementation Notes:
% 1. The function computes an N-point FFT of the first N samples of rx.
% 2. It then determines an offset (Delta) defined as:
% offset = round((1 - 1/eta) * N)
% 3. To avoid index overflow, the summation is taken over indices k from 1 to
% floor(N/2) - offset.
% 4. The timing error is estimated as:
% tau_error = ( (1+beta)/(2*eta*N - 1) * sum(phase difference) ) / (2*pi)
% where the phase difference is (angle(R(k)) - angle(R(k+offset)))
%
% Make sure that the input signal rx contains at least N samples.
% Check input length
if length(rx) < N
error('Input signal length must be at least N.');
end
% Compute the N-point FFT of the first N samples of rx
R = fft(rx(1:N), N);
% Determine the offset based on the oversampling factor (eta)
offset = round((1 - 1/eta) * N);
% Define the summation range to avoid index overflow
k_min = 1;
k_max = floor(N/2) - offset;
if k_max < k_min
error('Chosen parameters result in an empty summation range. Adjust N, eta, or beta.');
end
% Compute the sum of phase differences over the selected frequency bins
phase_diff_sum = 0;
for k = k_min:k_max
phase_k = angle(R(k));
phase_k_offset = angle(R(k + offset));
phase_diff_sum = phase_diff_sum + (phase_k - phase_k_offset);
end
% Normalization factor as per the modified Godard algorithm
norm_factor = (1 + beta) / (2 * eta * N - 1);
% Estimate the timing error in sample units
tau_error = (norm_factor * phase_diff_sum) / (2 * pi);
end