BCJR implementation
WDM code added (Pol Cont., Opt MUX/DEMUX, Opt Atten, DP_Fiber) -> the codebase is not optimized to always work with dp signals!
This commit is contained in:
Silas Oettinghaus
@@ -6,10 +6,10 @@ Symbols = load("imdd_simulation\projects\ECOC_2025\dsp_test\pam4_symbols.mat");S
|
||||
|
||||
eq_ = FFE_DCremoval("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",1e-5,"mu_tr",0,"order",50,"sps",2,"decide",0,"mu_dc",0.005,"dc_buffer_len",1);
|
||||
|
||||
savePath = 'Z:\2025\ECOC Silas\ecoc_2025\';
|
||||
databasePath = 'C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
|
||||
database_name = 'ecoc2025_loops.db';
|
||||
db = DBHandler("type","mysql");
|
||||
% savePath = 'Z:\2025\ECOC Silas\ecoc_2025\';
|
||||
% databasePath = 'C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
|
||||
% database_name = 'ecoc2025_loops.db';
|
||||
% db = DBHandler("type","mysql");
|
||||
|
||||
params = (logspace(-6,-2,20));
|
||||
params = floor((logspace(2,3,20)));
|
||||
@@ -19,16 +19,16 @@ for i = 1:length(params)
|
||||
|
||||
eq_ = FFE_DCremoval_adaptive_mu("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
|
||||
0.0002,"mu_tr",0,"order",25,"sps",2,"decide",0,...
|
||||
"mu_dc",0.005,"dc_buffer_len",224, ...
|
||||
"mu_dc",0.005,"dc_buffer_len",1, ...
|
||||
"ffe_buffer_len",1,...
|
||||
"smoothing_buffer_length",0,...
|
||||
"smoothing_buffer_update",224);
|
||||
"smoothing_buffer_update",1);
|
||||
|
||||
result = vnle(eq_,4,Scpe_sig,Symbols,Tx_bits,"precode_mode",db_mode.no_db,'showAnalysis',1,"postFFE",[],"eth_style_symbol_mapping",0);
|
||||
ber_ffe(i) = result.ber_vnle;
|
||||
result = ffe(eq_,4,Scpe_sig,Symbols,Tx_bits,"precode_mode",db_mode.no_db,'showAnalysis',1,"postFFE",[],"eth_style_symbol_mapping",0);
|
||||
ber_ffe(i) = result.metrics;
|
||||
fprintf(" FFE Results: %.2e\n", ber_ffe(i));
|
||||
|
||||
db.addProcessingResult(run_id, result.resultsVNLE, result.equalizerConfigVNLE);
|
||||
% db.addProcessingResult(run_id, result.resultsVNLE, result.equalizerConfigVNLE);
|
||||
|
||||
% eq_ = FFE_adaptive_decision("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
|
||||
% 0.0003,"mu_tr",0,"order",50,"sps",2,"decide",1,"buffer_length",params(i));
|
||||
|
||||
@@ -1,25 +1,24 @@
|
||||
|
||||
basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
|
||||
% basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
|
||||
% database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
|
||||
database = DBHandler("type",'mysql');
|
||||
database = DBHandler("type",'mysql','dataBase','labor');
|
||||
|
||||
filterParams = database.tables;
|
||||
%filterParams.Runs.loop_id = 209;
|
||||
filterParams.Configurations = struct( ...
|
||||
'symbolrate', 112e9, ... %[224,336,360,390,420,448]
|
||||
'fiber_length', 0, ...
|
||||
'db_mode', '"no_db"', ...
|
||||
'interference_attenuation', [], ...
|
||||
'interference_path_length', [], ...
|
||||
'is_mpi', 1, ...
|
||||
'pam_level', 4, ...
|
||||
'wavelength', 1310, ...
|
||||
'precomp_amp', [], ...
|
||||
'signal_attenuation', [], ...
|
||||
'v_awg', [], ...
|
||||
'v_bias', [] ...
|
||||
);
|
||||
|
||||
filterParams.Runs.loop_id = 209;
|
||||
% filterParams.Configurations = struct( ...
|
||||
% 'symbolrate', 112e9, ... %[224,336,360,390,420,448]
|
||||
% 'fiber_length', 0, ...
|
||||
% 'db_mode', '"no_db"', ...
|
||||
% 'interference_attenuation', [], ...
|
||||
% 'interference_path_length', 1000, ...
|
||||
% 'is_mpi', 1, ...
|
||||
% 'pam_level', 4, ...
|
||||
% 'wavelength', 1310, ...
|
||||
% 'precomp_amp', [], ...
|
||||
% 'signal_attenuation', [], ...
|
||||
% 'v_awg', [], ...
|
||||
% 'v_bias', [] ...
|
||||
% );
|
||||
|
||||
% if 1
|
||||
% % filterParams.EqualizerParameters.dc_buffer_len = 1;
|
||||
@@ -28,9 +27,15 @@ filterParams.Configurations = struct( ...
|
||||
% filterParams.EqualizerParameters.smoothing_buffer_update = 224;
|
||||
% filterParams.EqualizerParameters.DCmu = 0;
|
||||
% end
|
||||
a = database.getTableFieldNames('Runs');
|
||||
b = database.getTableFieldNames('Results');
|
||||
c = database.getTableFieldNames('EqualizerParameters');
|
||||
d = [a;b;c];
|
||||
|
||||
selectedFields = {'Configurations.run_id' 'Runs.loop_id' 'Runs.date_of_run' 'Runs.rx_raw_path' 'Configurations.bitrate' 'Configurations.v_bias' 'Configurations.v_awg' 'Configurations.precomp_amp' 'Configurations.symbolrate' 'Configurations.pam_level'...
|
||||
'Configurations.db_mode' 'Configurations.rop_attenuation' 'Configurations.is_mpi' 'Configurations.interference_attenuation' 'Configurations.interference_path_length' 'Configurations.signal_attenuation' ...
|
||||
[dataTable,~] = database.queryDB(filterParams, d);
|
||||
|
||||
selectedFields = {'Configurations.run_id' 'Runs.loop_id' 'Runs.date_of_run' 'Runs.rx_raw_path' 'Runs.bitrate' 'Runs.v_bias' 'Runs.v_awg' 'Runs.precomp_amp' 'Runs.symbolrate' 'Runs.pam_level'...
|
||||
'Runs.db_mode' 'Runs.rop_attenuation' 'Runs.is_mpi' 'Runs.interference_attenuation' 'Runs.interference_path_length' 'Runs.signal_attenuation' ...
|
||||
'EqualizerParameters.equalizer_structure' 'EqualizerParameters.diff_precode' 'EqualizerParameters.eq_id' 'EqualizerParameters.dc_buffer_len' 'EqualizerParameters.ffe_buffer_len' 'EqualizerParameters.smoothing_buffer_len' 'EqualizerParameters.smoothing_buffer_update' 'EqualizerParameters.DCmu' 'Measurements.power_pd_in' ...
|
||||
'Measurements.power_mpi_interference' 'Measurements.power_mpi_signal' 'Results.BER' 'Results.BER_precoded' 'Results.EVM' 'Results.SNR' 'Results.GMI' 'Results.Alpha' 'Results.date_of_processing'};
|
||||
|
||||
|
||||
82
projects/ECOC_2025/theory/analytic_mpi_evaluation.m
Normal file
82
projects/ECOC_2025/theory/analytic_mpi_evaluation.m
Normal file
@@ -0,0 +1,82 @@
|
||||
% This script is used to evaluate Fig. 1b) in the paper "Adaptive Removal of Multipath Interference in Short Reach 112 GBd PAM-4 IM/DD Systems"
|
||||
|
||||
%% Parameters
|
||||
df = 1e6;%150e3; % Laser linewidth [Hz]
|
||||
SIR_dB = 20; % Interference attenuation [dB]
|
||||
alpha = 10^(-SIR_dB/20); % Interference attenuation [linear]
|
||||
n_fiber = 1.467; % Refractive index
|
||||
c = physconst('lightspeed'); % [m/s]
|
||||
|
||||
L = linspace(0,400,40); % Interference delay [m]
|
||||
tau = n_fiber./c.*L; % Interference time (= tau) [s]
|
||||
|
||||
tau_c = 1/(pi*df); % laser coherence time [s]
|
||||
L_c = (c/n_fiber)*tau_c; % laser coherence length [m]
|
||||
|
||||
var_sat = 2*alpha^2; % Analytical saturation of variance
|
||||
|
||||
%% Monte–Carlo Simulation
|
||||
fs = 100e9; % sampling rate [Hz]
|
||||
Tsim = 50e-6; % sim duration [s]
|
||||
N = round(Tsim*fs); % number of samples for each realization
|
||||
max_delay_samples = round(max(tau)*fs); % largest delay that is evaluated (based on max. Interference delay)
|
||||
phase_noise_std = sqrt(2*pi*df/fs); % standard dev. phase noise
|
||||
|
||||
num_realizations = 10; % number of parallel runs
|
||||
monte_carlo_variance = zeros(num_realizations, length(L));
|
||||
parfor r = 1:num_realizations
|
||||
|
||||
% generate a realization of phase noise random walk
|
||||
dphi = phase_noise_std * randn(1, N + max_delay_samples); % matlab randn process has std = 1
|
||||
phi = cumsum(dphi);
|
||||
phi_direct = phi(max_delay_samples+1 : max_delay_samples+N);
|
||||
var_k = zeros(1, length(L));
|
||||
for t = 1:length(tau)
|
||||
|
||||
nd = round( tau(t)*fs ); % delay in samples for current interference time
|
||||
phi_delayed = phi(max_delay_samples+1-nd : max_delay_samples+N-nd); %cut out interfering signal part (was earlier)
|
||||
|
||||
E = exp(1j*phi_direct) + alpha*exp(1j*phi_delayed); % E-fields combined
|
||||
I = abs(E).^2; % photo current as magnitude square of E-field
|
||||
var_k(t) = var(I);
|
||||
|
||||
end
|
||||
monte_carlo_variance(r, :) = var_k;
|
||||
end
|
||||
|
||||
avg_of_mc_variances = mean(monte_carlo_variance, 1);
|
||||
std_of_mc_variances = std(monte_carlo_variance, 0, 1);
|
||||
|
||||
%% Analytic variance
|
||||
analytic_variance = 2*alpha^2 * (1 - exp(-2*pi*df.*tau)).^2;
|
||||
|
||||
%% Plot
|
||||
cols = [0.3467 0.5360 0.6907
|
||||
0.9153 0.2816 0.2878
|
||||
0.4416 0.7490 0.4322];
|
||||
|
||||
coherence_length_multiples = 0.5:0.5:ceil(L(end)/L_c);
|
||||
|
||||
figure();
|
||||
hold on;
|
||||
plot(L, avg_of_mc_variances, 'LineWidth',2, 'DisplayName','Simulation','Color',cols(1,:),'LineStyle','-');
|
||||
errorbar(L, avg_of_mc_variances,std_of_mc_variances, 'LineWidth',0.7,'LineStyle','none', 'DisplayName','Simulation','Color',cols(1,:),'HandleVisibility','off');
|
||||
|
||||
plot(L, analytic_variance, 'LineWidth',2, 'DisplayName','Analytic','Color',cols(2,:),'LineStyle','-');
|
||||
xticks(coherence_length_multiples.*L_c);
|
||||
xticklabels(round(coherence_length_multiples.*L_c));
|
||||
|
||||
norm_to_coherence_len = 1;
|
||||
if norm_to_coherence_len
|
||||
xticklabels(coherence_length_multiples);
|
||||
xlabel('$\tau_c$', 'FontSize',12);
|
||||
end
|
||||
|
||||
xline(L_c.*coherence_length_multiples, 'LineWidth',1.5, 'DisplayName','Coh. Length','HandleVisibility','off','Color',[0.7,0.7,0.7],'LineStyle','-');
|
||||
xlim([0,L(end)]);
|
||||
yline(var_sat, '-.k','LineWidth',1.5, 'DisplayName','Saturation: 2$\alpha ^2$');
|
||||
xlabel('Interference Delay [m]', 'FontSize',12);
|
||||
grid on;
|
||||
ylabel('Intensity Variance', 'FontSize',12);
|
||||
title(sprintf('MPI Variance; %d MHz; SIR: %d dB',df.*1e-6,SIR_dB), 'FontSize',14);
|
||||
legend('Location','southeast');
|
||||
32
projects/ECOC_2025/theory/coherence_length_plot.m
Normal file
32
projects/ECOC_2025/theory/coherence_length_plot.m
Normal file
@@ -0,0 +1,32 @@
|
||||
%% Parameters
|
||||
df = linspace(100e3,50e6,10000); % Laser FWHM linewidth [Hz]
|
||||
n_fiber = 1.467; % Fiber group index
|
||||
c = 3e8; % Speed of light [m/s]
|
||||
|
||||
% Compute coherence length (1/e of mean-fringe decay)
|
||||
tau_c = 1./(pi*df);
|
||||
L_c = (c/n_fiber) .* tau_c; % Coherence length [m]
|
||||
|
||||
%% Plot
|
||||
figure('Color','w');
|
||||
loglog(df/1e6, L_c, 'LineWidth',2,'LineStyle','-'); % linewidth in MHz
|
||||
xticks([0.1, 1, 10, 50]);
|
||||
yticks([1, 10, 100, 1000]);
|
||||
yticklabels({'1','10','100','1000'})
|
||||
grid on; box on;
|
||||
xlabel('Laser linewidth [MHz]','FontSize',12,'Interpreter','none');
|
||||
ylabel('Coherence length [m]','FontSize',12,'Interpreter','none');
|
||||
title('Coherence Length vs. Laser Linewidth','FontSize',14,'Interpreter','none');
|
||||
|
||||
%% Annotate some key points
|
||||
hold on;
|
||||
freqs = [150e3, 1e6, 10e6, 50e6]; % [Hz]
|
||||
for f = freqs
|
||||
x = f/1e6;
|
||||
y = (c/n_fiber) * (1/(pi*f));
|
||||
scatter(x,y,'Marker','x','LineWidth',1,'MarkerEdgeColor','black');
|
||||
|
||||
text(x*1.1,y, sprintf('%.2f MHz', f/1e6), ...
|
||||
'FontSize',10,'HorizontalAlignment','left');
|
||||
|
||||
end
|
||||
Reference in New Issue
Block a user