Add new functions
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Silas Oettinghaus
150
Functions/EQ_visuals/analyzeEQperformance.m
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150
Functions/EQ_visuals/analyzeEQperformance.m
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function analyzeEQperformance(ref_bits,ref_symbols,rx_signal,eq_signal,eq_decisions,fsym,M,options)
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arguments
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ref_bits
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ref_symbols
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rx_signal
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eq_signal
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eq_decisions
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fsym
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M
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options.postfilterclass
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options.eqclass
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options.mlseclass
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options.db_precoded
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options.displayname
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end
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% toolkit to visualize stuff related to DSP of IM/DD
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%%% Preps
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if isempty(eq_decisions)
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eq_decisions = PAMmapper(M,0).quantize(eq_signal);
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end
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%%% Demap eqlzd signal to determine BER
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if options.db_precoded
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eq_hd = PAMmapper(M,0).quantize(eq_signal);
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eq_hd = Duobinary().encode(eq_hd);
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eq_hd = Duobinary().decode(eq_hd,"M",M);
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rx_bits = PAMmapper(M,0).demap(eq_hd);
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else
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rx_bits = PAMmapper(M,0).demap(eq_signal);
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end
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[~,numerr,ber_sd,errpos] = calc_ber(rx_bits.signal,ref_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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% fprintf('SD BER: %.2e \n',ber_sd);
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%%% Demap provided decisions to determine BER
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rx_bits = PAMmapper(M,0).demap(eq_decisions);
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[~,numerr,ber_mlse,errpos] = calc_ber(rx_bits.signal,ref_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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% fprintf('MLSE BER: %.2e \n',ber_mlse);
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%%% Noise prior to DSP (is thius accurate with resampling?)
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rx_resampled = rx_signal.normalize("mode","rms").resample("fs_out",fsym);
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rx_noise = rx_resampled-ref_symbols;
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%%% Noise after to soft-decision DSP
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eq_noise = eq_signal-ref_symbols;
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col = cbrewer2('paired',12);
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lines = numel(findall(figure(200), 'Type', 'Line'))+1;
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darkcoloridx = max(mod(2*lines,12),2);
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lightcoloridx = max(mod(2*lines-1,12),1);
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%%% Separate Classes
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constellation = unique(ref_symbols.signal);
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received_sd = NaN(numel(constellation),length(ref_symbols));
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received_hd = NaN(numel(constellation),length(ref_symbols));
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lvlcol = cbrewer2('Set1',numel(constellation));
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for lvl = 1:numel(constellation)
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%Separate the equalized signal into the
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%respective levels based on the actually
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%transmitted level!
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received_sd(lvl,ref_symbols.signal==constellation(lvl)) = eq_signal.signal(ref_symbols.signal==constellation(lvl));
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received_hd(lvl,ref_symbols.signal==constellation(lvl)) = eq_decisions.signal(ref_symbols.signal==constellation(lvl));
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end
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%%% bursts
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% Find differences between consecutive elements
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diff_indices = diff(errpos);
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% Identify the start of new sequences (when the difference is not 1)
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sequence_starts = [1, find(diff_indices ~= 1) + 1]; % Include the first index
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sequence_ends = [sequence_starts(2:end) - 1, length(errpos)]; % Calculate end indices
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% Initialize burst count and print bursts longer than 10
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burst_len = 1:10;
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burst_count = zeros(length(burst_len),1);
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for t = 1:numel(burst_len)
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for i = 1:length(sequence_starts)
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% Extract current sequence
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current_burst = errpos(sequence_starts(i):sequence_ends(i));
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% Check if the sequence length matches criterion
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if length(current_burst) == burst_len(t)
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burst_count(t) = burst_count(t) + 1;
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end
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end
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end
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burst_symbols = burst_count .* burst_len';
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burst_rate = burst_symbols ;%./ length(rx_signal);
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%% Rx Spectrum %200
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rx_signal.spectrum("displayname",sprintf('Rx %d GBd PAM%d',fsym.*1e-9,M),'fignum',200,'normalizeTo0dB',1,'color',col(darkcoloridx,:));
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xline([-fsym/2,fsym/2].*1e-9,'Color',col(mod(lines,12)+2,:),'HandleVisibility','off');
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ylim([-20,3]);
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%%% EQ Spectrum
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%
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%%% EQ Time Series %210
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showEQTimeSignal(eq_signal,ref_symbols)
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%%% EQ Noise Spectrum + inverted Postfilter %220
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showEQNoisePSD(eq_noise,options.postfilterclass.burg_coeff,"fignum",220,"color",col(darkcoloridx,:));
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%%% EQ SNR Spectrum %230
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fft_length = 2^13;
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[s_lin,w] = pwelch(eq_signal.signal,hanning(fft_length),fft_length/2,fft_length,eq_signal.fs,"centered","psd","mean");
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[n_lin,w] = pwelch(eq_noise.signal,hanning(fft_length),fft_length/2,fft_length,eq_noise.fs,"centered","psd","mean");
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w = w.*1e-9;
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snr_dbm = 10*log10(s_lin./n_lin);
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figure(230)
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hold on
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plot(w,snr_dbm,'DisplayName','SNR after EQ','LineWidth',1,'Color',col(darkcoloridx,:));
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xlabel("Frequency in GHz");
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edgetick = 2^(nextpow2(eq_signal.fs*1e-9));
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xticks(-edgetick:16:edgetick);
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xlim([-128 128]);
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ylim([-20,35]);
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grid minor
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yticks(-200:10:100);
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grid on; grid minor;
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legend('Interpreter','none');
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title('Noise of soft decision signal (not MLSE)');
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%%% FFE histogram %240
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showLevelHistogram(eq_signal,ref_symbols)
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%%% Confusion Matrix
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showLevelConfusionMatrix(eq_decisions,ref_symbols,"fignum",250)
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%%% Burst Count
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figure(260)
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hold on
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plot(burst_len,burst_rate,'Marker','x','Color',col(darkcoloridx,:),"displayname",sprintf('Rx %d GBd PAM%d; %s',fsym.*1e-9,M,options.displayname));
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xlabel('length of error burst');
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ylabel('occurences')
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grid on
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set(gca, 'YScale', 'log');
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autoArrangeFigures
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end
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