Many changes towards simulation of JLT and once again the evaluation of the Highspeed data from Lab experiments 2024
This commit is contained in:
Silas Oettinghaus
60
projects/ECOC_2025/auswertung_algorithms/mpi_dsp_debug.m
Normal file
60
projects/ECOC_2025/auswertung_algorithms/mpi_dsp_debug.m
Normal file
@@ -0,0 +1,60 @@
|
||||
|
||||
load("ffe_debug_snapshot.mat");
|
||||
|
||||
|
||||
dc_buffer_len = logspace(0,3,12);
|
||||
dc_buffer_len = 1024;
|
||||
|
||||
mu_dc = logspace(-3,0,24);
|
||||
|
||||
parfor d = 1:length(mu_dc)
|
||||
|
||||
eq_lin = 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",mu_dc(d),...
|
||||
"dc_buffer_len",1024, ...
|
||||
"ffe_buffer_len",1,...
|
||||
"smoothing_buffer_length",0,...
|
||||
"smoothing_buffer_update",1,...
|
||||
"adaptive_mu_mode",0);
|
||||
%
|
||||
% eq_lin = FFE("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
|
||||
% 0.0002,"mu_tr",0,"order",25,"sps",2,"decide",0);
|
||||
|
||||
ffe_results = ffe(eq_lin,M,Scpe_sig,Symbols,Tx_bits,...
|
||||
"precode_mode",duob_mode,...
|
||||
'showAnalysis',0,...
|
||||
"postFFE",[],...
|
||||
"eth_style_symbol_mapping",0);
|
||||
|
||||
ffe_results.metrics.print
|
||||
|
||||
% % eq_lin = FFE_DFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"ffe_mu_dd",1e-4,"dfe_mu_dd",5e-4,"ffe_mu_tr",0,"dfe_mu_tr",0,"ffe_order",21,"dfe_order",2,"sps",2,"decide",0);
|
||||
%
|
||||
% eq_lin = FFE("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
|
||||
% 0.0002,"mu_tr",0,"order",25,"sps",2,"decide",0);
|
||||
% pf_ = Postfilter("ncoeff",2,"useBurg",1);
|
||||
% mlse_ = MLSE_viterbi("duobinary_output",0,'M',4,'trellis_states',PAMmapper(4,0).levels);
|
||||
%
|
||||
% [ffe_results2, mlse_results] = vnle_postfilter_mlse(eq_lin, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
|
||||
% "precode_mode", duob_mode,...
|
||||
% 'showAnalysis', 1, ...
|
||||
% "postFFE", [],...
|
||||
% "eth_style_symbol_mapping", 0);
|
||||
|
||||
ber(d) = ffe_results.metrics.BER;
|
||||
|
||||
|
||||
end
|
||||
|
||||
figure(10)
|
||||
hold on
|
||||
plot(mu_dc,ber,'LineWidth',1,'DisplayName',sprintf('DC buffer len = 1024'),'Marker','.','MarkerSize',10);
|
||||
xlabel('BER');
|
||||
xlabel('MU DC');
|
||||
title('BER Optimization over dc\_buffer\_len');
|
||||
yline([4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
|
||||
ylim([9e-4, 0.5]);
|
||||
set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
|
||||
legend('show', 'Location', 'best');
|
||||
grid on;
|
||||
118
projects/ECOC_2025/auswertung_algorithms/run_offline_dsp.m
Normal file
118
projects/ECOC_2025/auswertung_algorithms/run_offline_dsp.m
Normal file
@@ -0,0 +1,118 @@
|
||||
% === SETTINGS ===
|
||||
|
||||
dsp_options.append_to_db = 0;
|
||||
dsp_options.max_occurences = 15;
|
||||
dsp_options.database_path = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
|
||||
dsp_options.database_name = 'silas_labor_newdsp_newstructure.db';
|
||||
dsp_options.storage_path = 'Z:\2024\sioe_labor\';
|
||||
|
||||
dsp_options.parameters = struct();
|
||||
dsp_options.parameters.mu_dc = [0.005];
|
||||
|
||||
% === Get Run ID's ===
|
||||
db = DBHandler("pathToDB", [dsp_options.database_path, dsp_options.database_name], "type", "sqlite");
|
||||
fp = QueryFilter();
|
||||
% fp.where('Runs', 'run_id','EQUALS', 5108);
|
||||
fp.where('Runs', 'is_mpi','EQUALS', 0);
|
||||
fp.where('Runs', 'fiber_length','EQUALS', 1);
|
||||
fp.where('Runs', 'wavelength','EQUALS', 1310);
|
||||
fp.where('Runs', 'db_mode','EQUALS', 1);
|
||||
fp.where('Runs', 'rop_attenuation','EQUALS', 0);
|
||||
fp.where('Runs', 'pam_level','EQUALS', 4);
|
||||
fp.where('Runs', 'bitrate','EQUALS', 360e9);
|
||||
% fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
|
||||
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
|
||||
|
||||
% === Initialize DataStorage ===
|
||||
wh = DataStorage(dsp_options.parameters);
|
||||
wh.addStorage("ffe_package");
|
||||
wh.addStorage("mlse_package");
|
||||
wh.addStorage("vnle_package");
|
||||
wh.addStorage("dbtgt_package");
|
||||
wh.addStorage("dbenc_package");
|
||||
|
||||
% === RUN IT ===
|
||||
|
||||
% [results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "serial", 'wh', wh, 'waitbar', true);
|
||||
% wh.getStoValue('ffe_package',0.005);
|
||||
% wh.getStoValue('mlse_package',0.005);
|
||||
|
||||
[dataTable,~] = db.queryDB(fp, [db.getTableFieldNames('Runs');db.getTableFieldNames('Results');db.getTableFieldNames('Equalizer')]);
|
||||
|
||||
dataTable = cleanUpTable(dataTable);
|
||||
|
||||
% === Look at it ===
|
||||
y_var = 'BER_precoded';
|
||||
x_var = 'bitrate';
|
||||
fixedVars = {'equalizer_structure', x_var};
|
||||
|
||||
[dataTableClean, outliersTable] = removeGroupOutliers(dataTable, fixedVars, y_var);
|
||||
|
||||
% --- Group and aggregate ---
|
||||
dataTableGrpd_mean = groupIt(fixedVars, dataTableClean, @mean);
|
||||
dataTableGrpd_min = groupIt(fixedVars, dataTableClean, @min);
|
||||
dataTableGrpd_max = groupIt(fixedVars, dataTableClean, @max);
|
||||
|
||||
% Choose a color map
|
||||
cols = linspecer(numel(unique(dataTableGrpd_mean.equalizer_structure)));
|
||||
|
||||
figure;
|
||||
hold on;
|
||||
|
||||
% Get unique equalizer structures for grouping
|
||||
unique_eq = unique(dataTableGrpd_mean.equalizer_structure);
|
||||
|
||||
for i = 1:numel(unique_eq)
|
||||
eq_val = unique_eq(i);
|
||||
|
||||
% Filter grouped data for this equalizer structure
|
||||
filt = dataTableGrpd_mean.equalizer_structure == eq_val;
|
||||
|
||||
x = dataTableGrpd_mean.(x_var)(filt);
|
||||
y_mean = dataTableGrpd_mean.(y_var)(filt);
|
||||
y_min = dataTableGrpd_min.(y_var)(filt);
|
||||
y_max = dataTableGrpd_max.(y_var)(filt);
|
||||
|
||||
% Bounds for boundedline (distance from mean)
|
||||
y_lower = y_mean - y_min;
|
||||
y_upper = y_max - y_mean;
|
||||
y_bounds = [y_lower, y_upper];
|
||||
|
||||
% --- Bounded line (mean ± min/max) ---
|
||||
if exist('boundedline', 'file')
|
||||
[hl, hp] = boundedline(x, y_mean, y_bounds, ...
|
||||
'alpha', 'transparency', 0.1, ...
|
||||
'cmap', cols(i,:), ...
|
||||
'nan', 'fill', ...
|
||||
'orientation', 'vert');
|
||||
set(hl, 'LineWidth', 1.2, 'DisplayName', sprintf('Eq %s', eq_val));
|
||||
set(hp, 'HandleVisibility', 'off');
|
||||
else
|
||||
% If boundedline is not available, use errorbar
|
||||
errorbar(x, y_mean, y_lower, y_upper, ...
|
||||
'o-', 'Color', cols(i,:), 'LineWidth', 1.2, ...
|
||||
'DisplayName', sprintf('Eq %d', eq_val),'HandleVisibility', 'off');
|
||||
end
|
||||
|
||||
% --- Normal line (mean only) ---
|
||||
plot(x, y_mean, '-', 'Color', cols(i,:), 'LineWidth', 1.5, ...
|
||||
'DisplayName', sprintf('Mean Eq %s', eq_val),'HandleVisibility', 'off');
|
||||
|
||||
% --- Scatter plot for individual points (from original data) ---
|
||||
% Filter original data for this group
|
||||
orig_filt = dataTableClean.equalizer_structure == eq_val;
|
||||
x_scatter = dataTableClean.(x_var)(orig_filt);
|
||||
y_scatter = dataTableClean.(y_var)(orig_filt);
|
||||
|
||||
scatter(x_scatter, y_scatter, 10,cols(i,:), 'filled', ...
|
||||
'MarkerFaceAlpha', 0.5, 'DisplayName', sprintf('Scatter Eq %s', eq_val),'HandleVisibility', 'off');
|
||||
end
|
||||
|
||||
yline([2.2e-4,4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
|
||||
set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
|
||||
xlabel(x_var, 'Interpreter', 'none');
|
||||
ylabel(y_var, 'Interpreter', 'none');
|
||||
legend('show', 'Location', 'best');
|
||||
grid on;
|
||||
title(sprintf('%s vs. %s', y_var, x_var), 'Interpreter', 'none');
|
||||
hold off;
|
||||
@@ -0,0 +1,224 @@
|
||||
% === SETTINGS ===
|
||||
dsp_options.append_to_db = 1;
|
||||
dsp_options.max_occurences = 1;
|
||||
|
||||
experiment = "highspeed_2024";
|
||||
dsp_options.mode = "load_run_id"; % 'simulate' & 'load_files'
|
||||
dsp_options.load_file_path = struct();
|
||||
|
||||
if dsp_options.mode == "load_run_id"
|
||||
|
||||
if experiment == "highspeed_2024"
|
||||
|
||||
dsp_options.database_type = 'mysql';
|
||||
dsp_options.dataBase = 'labor_highspeed';%'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\silas_labor_newdsp_newstructure.db';
|
||||
dsp_options.storage_path = 'Z:\2024\sioe_labor\';
|
||||
db = DBHandler("dataBase", [dsp_options.dataBase], "type", dsp_options.database_type);
|
||||
|
||||
elseif experiment == "mpi_ecoc_2025"
|
||||
|
||||
dsp_options.database_type = 'mysql';
|
||||
dsp_options.dataBase = 'labor';
|
||||
dsp_options.storage_path = 'Z:\2025\ECOC Silas\ecoc_2025\';
|
||||
db = DBHandler("dataBase", [dsp_options.dataBase], "type", dsp_options.database_type);
|
||||
|
||||
end
|
||||
|
||||
elseif dsp_options.mode == "load_files"
|
||||
|
||||
dsp_options.load_file_path.tx_bits_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091513_PAM_4_R_112_bits.mat"';
|
||||
dsp_options.load_file_path.tx_symbols_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091513_PAM_4_R_112_symbols.mat"';
|
||||
dsp_options.load_file_path.rx_raw_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091525_PAM_4_R_112_rec01_rx_signal_raw.mat"';
|
||||
|
||||
elseif dsp_options.mode == "simulate"
|
||||
|
||||
error('Not yet implemented')
|
||||
|
||||
end
|
||||
|
||||
% === Get Run ID's ===
|
||||
|
||||
fp = QueryFilter();
|
||||
% fp.where('Runs', 'run_id','EQUALS', 987);
|
||||
% fp.where('Runs', 'pam_level','EQUALS', 4);
|
||||
fp.where('Runs', 'bitrate','LESS_THAN', 310e9);
|
||||
fp.where('Runs', 'fiber_length','EQUALS', 1);
|
||||
fp.where('Runs', 'is_mpi','EQUALS', 0);
|
||||
% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
|
||||
% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
|
||||
% fp.where('Runs', 'sir','EQUALS',18);
|
||||
fp.where('Runs', 'wavelength','EQUALS', 1310);
|
||||
% fp.where('Runs', 'db_mode','EQUALS', 1);
|
||||
fp.where('Runs', 'rop_attenuation','EQUALS', 0);
|
||||
% fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
|
||||
|
||||
|
||||
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
|
||||
|
||||
|
||||
% Keep only the rows corresponding to the first occurrence of each 'sir' value
|
||||
% [~, unique_indices] = unique(dataTable.sir, 'first');
|
||||
% dataTable = dataTable(unique_indices, :);
|
||||
|
||||
% dataTable = dataTable(1,:);
|
||||
|
||||
% === Set LOOPS & Initialize DataStorage ===
|
||||
dsp_options.parameters = struct();
|
||||
% dsp_options.parameters.pf_ncoeffs = [1,2];%[0,logspace(-4,0,10)];
|
||||
|
||||
wh = DataStorage(dsp_options.parameters);
|
||||
wh.addStorage("ffe_package");
|
||||
wh.addStorage("mlse_package");
|
||||
wh.addStorage("vnle_package");
|
||||
wh.addStorage("dbtgt_package");
|
||||
wh.addStorage("dbenc_package");
|
||||
|
||||
% === RUN IT ===
|
||||
|
||||
[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "serial", 'wh', wh, 'waitbar', true);
|
||||
|
||||
|
||||
% wh.getStoValue('ffe_package',0.005);
|
||||
% wh.getStoValue('mlse_package',0.005);
|
||||
|
||||
% [dataTable,~] = db.queryDB(fp, [db.getTableFieldNames('Runs');db.getTableFieldNames('Results');db.getTableFieldNames('Equalizer')]);
|
||||
%
|
||||
% dataTable = cleanUpTable(dataTable);
|
||||
% wh_analyze = wh_adap;
|
||||
% % wh_analyze = wh_dcremoval_old2;
|
||||
% % wh_analyze = wh_dcremoval_old2;
|
||||
%
|
||||
% res = cell(wh_analyze.parameter.mu_dc.length,wh_analyze.parameter.dc_buffer_len.length);
|
||||
% ber_mean = zeros(wh_analyze.parameter.mu_dc.length,wh_analyze.parameter.dc_buffer_len.length);
|
||||
% for m = 1:wh_analyze.parameter.mu_dc.length
|
||||
% for b = 1:wh_analyze.parameter.dc_buffer_len.length
|
||||
% res{m,b}=wh_analyze.getStoValue("ffe_package",wh_analyze.parameter.mu_dc.values(m),wh_analyze.parameter.dc_buffer_len.values(b));
|
||||
% try
|
||||
% cells = res{m,b}{1};
|
||||
% idx = cellfun(@(c) ~isempty(c), cells);
|
||||
% ber = cellfun(@(c) c.metrics.BER, cells(idx));
|
||||
% ber_mean(m,b) = mean(ber);
|
||||
% catch
|
||||
% ber_mean(m,b) = NaN;
|
||||
% end
|
||||
% end
|
||||
% end
|
||||
%
|
||||
% figure()
|
||||
% hold on
|
||||
% ber_fix = cellfun(@(c) c.ffe_package{1}.metrics.BER, results_fix);
|
||||
% ber_adap_m2 = cellfun(@(c) c.ffe_package{1}.metrics.BER, results_adap);
|
||||
% ber_adap_method1 = cellfun(@(c) c.ffe_package{1}.metrics.BER, results);
|
||||
% plot(dataTable.sir,ber_fix,'LineWidth',1,'DisplayName',sprintf('DCt; fix mu = 0.5; p=1024'),'Marker','.','MarkerSize',10);
|
||||
% plot(dataTable.sir,ber_adap_method1,'LineWidth',1,'DisplayName',sprintf('DCt; adap mu 1; p=1024'),'Marker','.','MarkerSize',10);
|
||||
% plot(dataTable.sir,ber_adap_m2,'LineWidth',1,'DisplayName',sprintf('DCt; adap mu 2; p=1024'),'Marker','.','MarkerSize',10);
|
||||
% xlabel('BER');
|
||||
% xlabel('SIR');
|
||||
% yline([4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
|
||||
% % ylim([9e-4, 0.5]);
|
||||
% set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
|
||||
% legend('show', 'Location', 'best');
|
||||
% grid on;
|
||||
%
|
||||
%
|
||||
%
|
||||
%
|
||||
% figure; clf
|
||||
%
|
||||
% % Create meshgrid for contourf
|
||||
% [X, Y] = meshgrid(dsp_options.parameters.mu_dc, dsp_options.parameters.dc_buffer_len);
|
||||
%
|
||||
% % Create contour plot
|
||||
% contourf(X, Y, ber_mean', 20); % 20 contour levels, adjust as needed
|
||||
%
|
||||
% % Set axes to logarithmic scale
|
||||
% set(gca, 'XScale', 'log', 'YScale', 'log');
|
||||
%
|
||||
% colormap("parula");
|
||||
% c = colorbar;
|
||||
% c.Label.String = 'BER';
|
||||
%
|
||||
% xlabel('\mu_{dc}');
|
||||
% ylabel('dc\_buffer\_len');
|
||||
% title('BER Optimization over \mu_{dc} and dc\_buffer\_len');
|
||||
%
|
||||
% % Make plot prettier
|
||||
% grid on
|
||||
% set(gca, 'Layer', 'top'); % Put grid lines on top of contours
|
||||
%
|
||||
%
|
||||
% % === Look at it ===
|
||||
% y_var = 'BER_precoded';
|
||||
% x_var = 'bitrate';
|
||||
% fixedVars = {'equalizer_structure', x_var};
|
||||
%
|
||||
% [dataTableClean, outliersTable] = removeGroupOutliers(dataTable, fixedVars, y_var);
|
||||
%
|
||||
% % --- Group and aggregate ---
|
||||
% dataTableGrpd_mean = groupIt(fixedVars, dataTableClean, @mean);
|
||||
% dataTableGrpd_min = groupIt(fixedVars, dataTableClean, @min);
|
||||
% dataTableGrpd_max = groupIt(fixedVars, dataTableClean, @max);
|
||||
%
|
||||
% % Choose a color map
|
||||
% cols = linspecer(numel(unique(dataTableGrpd_mean.equalizer_structure)));
|
||||
%
|
||||
% figure;
|
||||
% hold on;
|
||||
%
|
||||
% % Get unique equalizer structures for grouping
|
||||
% unique_eq = unique(dataTableGrpd_mean.equalizer_structure);
|
||||
%
|
||||
% for i = 1:numel(unique_eq)
|
||||
% eq_val = unique_eq(i);
|
||||
%
|
||||
% % Filter grouped data for this equalizer structure
|
||||
% filt = dataTableGrpd_mean.equalizer_structure == eq_val;
|
||||
%
|
||||
% x = dataTableGrpd_mean.(x_var)(filt);
|
||||
% y_mean = dataTableGrpd_mean.(y_var)(filt);
|
||||
% y_min = dataTableGrpd_min.(y_var)(filt);
|
||||
% y_max = dataTableGrpd_max.(y_var)(filt);
|
||||
%
|
||||
% % Bounds for boundedline (distance from mean)
|
||||
% y_lower = y_mean - y_min;
|
||||
% y_upper = y_max - y_mean;
|
||||
% y_bounds = [y_lower, y_upper];
|
||||
%
|
||||
% % --- Bounded line (mean ± min/max) ---
|
||||
% if exist('boundedline', 'file')
|
||||
% [hl, hp] = boundedline(x, y_mean, y_bounds, ...
|
||||
% 'alpha', 'transparency', 0.1, ...
|
||||
% 'cmap', cols(i,:), ...
|
||||
% 'nan', 'fill', ...
|
||||
% 'orientation', 'vert');
|
||||
% set(hl, 'LineWidth', 1.2, 'DisplayName', sprintf('Eq %s', eq_val));
|
||||
% set(hp, 'HandleVisibility', 'off');
|
||||
% else
|
||||
% % If boundedline is not available, use errorbar
|
||||
% errorbar(x, y_mean, y_lower, y_upper, ...
|
||||
% 'o-', 'Color', cols(i,:), 'LineWidth', 1.2, ...
|
||||
% 'DisplayName', sprintf('Eq %d', eq_val),'HandleVisibility', 'off');
|
||||
% end
|
||||
%
|
||||
% % --- Normal line (mean only) ---
|
||||
% plot(x, y_mean, '-', 'Color', cols(i,:), 'LineWidth', 1.5, ...
|
||||
% 'DisplayName', sprintf('Mean Eq %s', eq_val),'HandleVisibility', 'off');
|
||||
%
|
||||
% % --- Scatter plot for individual points (from original data) ---
|
||||
% % Filter original data for this group
|
||||
% orig_filt = dataTableClean.equalizer_structure == eq_val;
|
||||
% x_scatter = dataTableClean.(x_var)(orig_filt);
|
||||
% y_scatter = dataTableClean.(y_var)(orig_filt);
|
||||
%
|
||||
% scatter(x_scatter, y_scatter, 10,cols(i,:), 'filled', ...
|
||||
% 'MarkerFaceAlpha', 0.5, 'DisplayName', sprintf('Scatter Eq %s', eq_val),'HandleVisibility', 'off');
|
||||
% end
|
||||
%
|
||||
% yline([2.2e-4,4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
|
||||
% set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
|
||||
% xlabel(x_var, 'Interpreter', 'none');
|
||||
% ylabel(y_var, 'Interpreter', 'none');
|
||||
% legend('show', 'Location', 'best');
|
||||
% grid on;
|
||||
% title(sprintf('%s vs. %s', y_var, x_var), 'Interpreter', 'none');
|
||||
% hold off;
|
||||
@@ -134,6 +134,7 @@ if fsym_ ~= fsym
|
||||
fsym = fsym_;
|
||||
% fprintf('Adapted symbolrate to %d GBd, to match provided bitrate of %d GBit/s using PAM %d \n',fsym.*1e-9,bitrate.*1e-9, M);
|
||||
end
|
||||
|
||||
f_nyquist = fsym/2;
|
||||
|
||||
%%% run the simulation or measurement or ...
|
||||
|
||||
227
projects/IMDD_base_system/simulation_bwl.m
Normal file
227
projects/IMDD_base_system/simulation_bwl.m
Normal file
@@ -0,0 +1,227 @@
|
||||
%%% Run parameters
|
||||
% TX
|
||||
M = 4;
|
||||
fsym = 180e9;
|
||||
|
||||
apply_pulsef = 1;
|
||||
fdac = 256e9;
|
||||
fadc = 256e9;
|
||||
random_key = 1;
|
||||
|
||||
db_precode = 0;
|
||||
db_encode = 0;
|
||||
|
||||
rcalpha = 0.05;
|
||||
kover = 16;
|
||||
vbias_rel = 0.5;
|
||||
u_pi = 2.9;
|
||||
vbias = -vbias_rel*u_pi;
|
||||
laser_wavelength = 1310;
|
||||
laser_linewidth = 0;
|
||||
tx_bw_nyquist = 0.6;
|
||||
rx_bw_nyquist = 0.6;
|
||||
|
||||
|
||||
% Channel
|
||||
link_length = 1;
|
||||
|
||||
% RX
|
||||
rop = -8;
|
||||
|
||||
|
||||
vnle_order1 = 50;
|
||||
vnle_order2 = 3;
|
||||
vnle_order3 = 3;
|
||||
|
||||
vnle_order=[vnle_order1,vnle_order2,vnle_order3];
|
||||
dfe_order = [0 0 0];
|
||||
|
||||
alpha = 0;
|
||||
|
||||
len_tr = 4096*2;
|
||||
|
||||
mu_ffe1 = 0.0001;
|
||||
mu_ffe2 = 0.0008;
|
||||
mu_ffe3 = 0.001;
|
||||
mu_dc = 0.005;
|
||||
% mu_dc = 0;
|
||||
|
||||
mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
|
||||
mu_dfe = 0.0004;
|
||||
|
||||
|
||||
dfe_ = sum(dfe_order)>0;
|
||||
|
||||
doub_mode = db_mode.no_db;
|
||||
|
||||
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
|
||||
|
||||
db_precode = 0;
|
||||
db_encode = 0;
|
||||
duob_mode = db_mode.no_db;
|
||||
apply_pulsef = 1;
|
||||
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
|
||||
"fsym",fsym,"M",M,"order",18,"useprbs",0,...
|
||||
"fs_out",fdac,...
|
||||
"applyclipping",0,"clipfactor",1.5,...
|
||||
"applypulseform",apply_pulsef,"pulseformer",Pform,...
|
||||
"randkey",random_key,...
|
||||
"db_precode",db_precode,"db_encode",db_encode,...
|
||||
"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
|
||||
|
||||
Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
|
||||
|
||||
|
||||
%%%%% AWG
|
||||
% El_sig = M8199A("kover",kover).process(Digi_sig);
|
||||
El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
|
||||
% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',0);
|
||||
% El_sig = El_sig.setPower(0,"dBm");
|
||||
|
||||
%%%%% Low-pass el. components %%%%%%
|
||||
f_nyquist = fsym/2;
|
||||
tx_bwl = tx_bw_nyquist.*f_nyquist;
|
||||
% tx_bwl = 80e9;
|
||||
El_sig = Filter('filtdegree',4,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
|
||||
% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',1);
|
||||
|
||||
%%%%% Electrical Driver Amplifier %%%%%%
|
||||
El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
|
||||
El_sig = El_sig.normalize("mode","oneone");
|
||||
|
||||
%%%%% MODULATE E/O CONVERSION %%%%%%
|
||||
[Opt_sig] = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs,"lambda",laser_wavelength,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",random_key+1).process(El_sig);
|
||||
|
||||
Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length/1000,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.07).process(Opt_sig);
|
||||
|
||||
|
||||
|
||||
rop = [-10];
|
||||
ber_vnle = [];
|
||||
ber_mlse = [];
|
||||
ber_viterbi = [];
|
||||
ber_db = [];
|
||||
ber_db_diff_precoded = [];
|
||||
gmi_vnle = [];
|
||||
gmi_mlse = [];
|
||||
gmi_mlse_db = [];
|
||||
|
||||
for r = 1:length(rop)
|
||||
|
||||
|
||||
%%%%%% ROP %%%%%%
|
||||
Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop(r)).process(Opt_sig);
|
||||
|
||||
%%%%%% PD Square Law %%%%%%
|
||||
Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11).process(Rx_sig);
|
||||
|
||||
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
|
||||
rx_bwl = rx_bw_nyquist.*f_nyquist;
|
||||
% rx_bwl = 80e9;
|
||||
Rx_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
|
||||
|
||||
% %%%%%% Low-pass Scope %%%%%%
|
||||
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
|
||||
|
||||
% Rx_sig.spectrum("displayname",'Analog Rx Spectrum','fignum',100,'normalizeTo0dB',1);
|
||||
|
||||
%%%%%% Scope %%%%%%
|
||||
Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
|
||||
"delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
|
||||
"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
|
||||
"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(Rx_sig);
|
||||
|
||||
Scpe_sig_resampled = Scpe_sig.resample("fs_out",2*fsym);
|
||||
|
||||
[~, Scpe_cell, ~, found_sync] = Scpe_sig_resampled.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
|
||||
|
||||
|
||||
eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_order3],"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);
|
||||
mlse_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels);
|
||||
|
||||
|
||||
%Duobinary Targeting
|
||||
if 0
|
||||
db_ref_sequence = Duobinary().encode(Symbols);
|
||||
db_ref_constellation = unique(db_ref_sequence.signal);
|
||||
[eq_signal, eq_noise] = eq_.process(Scpe_cell{1},db_ref_sequence);
|
||||
|
||||
mlse_.DIR = [1,1];
|
||||
[mlse_sig_sd,LLR,gmi_mlse_db(r)] = mlse_.process(eq_signal,Symbols);
|
||||
|
||||
mlse_sig_hd = PAMmapper(M,0,"eth_style",0).quantize(mlse_sig_sd);
|
||||
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(Symbols);
|
||||
tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
|
||||
|
||||
tx_bits_precoded = PAMmapper(M,0,"eth_style",0).demap(tx_symbols_precoded);
|
||||
|
||||
rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd_precoded);
|
||||
[~,errors_db_diff_precoded,ber_db_diff_precoded(r),~] = calc_ber(rx_bits_mlse.signal,tx_bits_precoded.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||||
|
||||
%B) Just determine BER
|
||||
rx_bits_mlse = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
|
||||
[bits_mlse,errors_mlse,ber_db(r),~] = calc_ber(rx_bits_mlse.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||||
end
|
||||
|
||||
% FFE or VNLE
|
||||
eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_order3],"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);
|
||||
[eq_signal_sd, eq_noise] = eq_.process(Scpe_cell{1}, Symbols);
|
||||
[gmi_vnle(r)] = calc_air(eq_signal_sd, Symbols, "skip_front", 100, "skip_end", 100);
|
||||
eq_signal_sd.plot("displayname",'bla','fignum',118);
|
||||
|
||||
% Hard decision on VNLE output
|
||||
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
|
||||
rx_bits = PAMmapper(M,0,"eth_style",0).demap(eq_signal_hd);
|
||||
[~,~,ber_vnle(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||||
fprintf('BER VNLE: %.2e \n',ber_vnle(r));
|
||||
fprintf('NGMI VNLE: %.2f \n',gmi_vnle(r)./log2(M));
|
||||
|
||||
|
||||
% Process through postfilter and MLSE
|
||||
pf_ncoeffs = 1;
|
||||
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
|
||||
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
|
||||
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
|
||||
mlse_.DIR = pf_.coefficients;
|
||||
[signalclass_hd,LLR,gmi_mlse(r)] = mlse_.process(mlse_sig_sd,Symbols);
|
||||
mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(signalclass_hd);
|
||||
rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
|
||||
[~,~,ber_mlse(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||||
fprintf('BER: %.2e \n',ber_mlse(r));
|
||||
fprintf('NGMI MLSE: %.2f \n',gmi_mlse(r)./log2(M));
|
||||
|
||||
|
||||
% Process through postfilter and MLSE
|
||||
pf_ncoeffs = 1;
|
||||
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
|
||||
mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
|
||||
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
|
||||
mlse_.DIR = pf_.coefficients;
|
||||
mlse_sig_sd = mlse_.process(mlse_sig_sd);
|
||||
mlse_sig_hd = PAMmapper(M, 0, "eth_style", 0).quantize(mlse_sig_sd);
|
||||
rx_bits = PAMmapper(M,0,"eth_style",0).demap(mlse_sig_hd);
|
||||
[~,~,ber_viterbi(r),~] = calc_ber(rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
|
||||
fprintf('FW BER: %.2e \n',ber_viterbi(r));
|
||||
|
||||
end
|
||||
|
||||
|
||||
figure();hold on
|
||||
plot(rop,gmi_mlse,'DisplayName','MLSE','Marker','*');
|
||||
plot(rop,gmi_vnle,'DisplayName','VNLE','Marker','*');
|
||||
plot(rop,gmi_mlse_db,'DisplayName','MLSE DB Tgt','Marker','*');
|
||||
ylim([0 2.6]);
|
||||
|
||||
figure();hold on
|
||||
plot(rop,ber_vnle,'DisplayName','VNLE');
|
||||
|
||||
plot(rop,ber_mlse,'DisplayName','MLSE','Marker','*');
|
||||
plot(rop,ber_viterbi,'DisplayName','Viterbi','Marker','*');
|
||||
plot(rop,ber_db_diff_precoded,'DisplayName','MLSE db diff','Marker','*');
|
||||
plot(rop,ber_db,'DisplayName','MLSE db','Marker','*');
|
||||
set(gca, 'yscale', 'log');
|
||||
legend
|
||||
144
projects/IMDD_base_system/simulation_bwl_2.m
Normal file
144
projects/IMDD_base_system/simulation_bwl_2.m
Normal file
@@ -0,0 +1,144 @@
|
||||
%%% Run parameters
|
||||
% TX
|
||||
M = 4;
|
||||
fsym = 180e9;
|
||||
|
||||
apply_pulsef = 1;
|
||||
fdac = 256e9;
|
||||
fadc = 256e9;
|
||||
random_key = 1;
|
||||
|
||||
db_precode = 0;
|
||||
db_encode = 0;
|
||||
|
||||
rcalpha = 0.05;
|
||||
kover = 16;
|
||||
vbias_rel = 0.5;
|
||||
u_pi = 2.9;
|
||||
vbias = -vbias_rel*u_pi;
|
||||
laser_wavelength = 1310;
|
||||
laser_linewidth = 0;
|
||||
tx_bw_nyquist = 0.7;
|
||||
|
||||
% Channel
|
||||
link_length = 1;
|
||||
|
||||
% RX
|
||||
rop = -8;
|
||||
rx_bw_nyquist = 0.7;
|
||||
|
||||
vnle_order1 = 50;
|
||||
vnle_order2 = 3;
|
||||
vnle_order3 = 3;
|
||||
|
||||
vnle_order=[vnle_order1,vnle_order2,vnle_order3];
|
||||
dfe_order = [0 0 0];
|
||||
|
||||
pf_ncoeffs = 1;
|
||||
|
||||
alpha = 0;
|
||||
|
||||
len_tr = 4096*2;
|
||||
|
||||
mu_ffe1 = 0.0001;
|
||||
mu_ffe2 = 0.0008;
|
||||
mu_ffe3 = 0.001;
|
||||
mu_dc = 0.005;
|
||||
% mu_dc = 0;
|
||||
|
||||
mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
|
||||
mu_dfe = 0.0004;
|
||||
|
||||
|
||||
dfe_ = sum(dfe_order)>0;
|
||||
|
||||
doub_mode = db_mode.no_db;
|
||||
|
||||
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
|
||||
|
||||
db_precode = 0;
|
||||
db_encode = 0;
|
||||
duob_mode = db_mode.no_db;
|
||||
apply_pulsef = 1;
|
||||
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
|
||||
"fsym",fsym,"M",M,"order",18,"useprbs",0,...
|
||||
"fs_out",fdac,...
|
||||
"applyclipping",0,"clipfactor",1.5,...
|
||||
"applypulseform",apply_pulsef,"pulseformer",Pform,...
|
||||
"randkey",random_key,...
|
||||
"db_precode",db_precode,"db_encode",db_encode,...
|
||||
"mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process();
|
||||
|
||||
Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
|
||||
|
||||
|
||||
|
||||
%%%%% AWG
|
||||
% El_sig = M8199A("kover",kover).process(Digi_sig);
|
||||
El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
|
||||
% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',0);
|
||||
% El_sig = El_sig.setPower(0,"dBm");
|
||||
|
||||
%%%%% Low-pass el. components %%%%%%
|
||||
f_nyquist = fsym/2;
|
||||
tx_bwl = tx_bw_nyquist.*f_nyquist;
|
||||
% tx_bwl = 80e9;
|
||||
El_sig = Filter('filtdegree',4,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
|
||||
% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',1);
|
||||
|
||||
%%%%% Electrical Driver Amplifier %%%%%%
|
||||
El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
|
||||
El_sig = El_sig.normalize("mode","oneone");
|
||||
|
||||
%%%%% MODULATE E/O CONVERSION %%%%%%
|
||||
[Opt_sig] = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs,"lambda",laser_wavelength,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",random_key+1).process(El_sig);
|
||||
|
||||
Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length/1000,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.07).process(Opt_sig);
|
||||
|
||||
%%%%%% ROP %%%%%%
|
||||
Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
|
||||
|
||||
%%%%%% PD Square Law %%%%%%
|
||||
Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11).process(Rx_sig);
|
||||
|
||||
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
|
||||
rx_bwl = rx_bw_nyquist.*f_nyquist;
|
||||
% rx_bwl = 80e9;
|
||||
Rx_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
|
||||
|
||||
% %%%%%% Low-pass Scope %%%%%%
|
||||
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
|
||||
|
||||
% Rx_sig.spectrum("displayname",'Analog Rx Spectrum','fignum',100,'normalizeTo0dB',1);
|
||||
|
||||
%%%%%% Scope %%%%%%
|
||||
Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
|
||||
"delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
|
||||
"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
|
||||
"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(Rx_sig);
|
||||
|
||||
Scpe_sig_resampled = Scpe_sig.resample("fs_out",2*fsym);
|
||||
|
||||
[~, Scpe_cell, ~, found_sync] = Scpe_sig_resampled.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
|
||||
|
||||
eq_ = EQ("Ne",[vnle_order1,vnle_order2,vnle_order3],"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);
|
||||
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);
|
||||
|
||||
% FFE or VNLE
|
||||
[eq_signal_sd, eq_noise] = eq_.process(Scpe_cell{1}, Symbols);
|
||||
|
||||
% Hard decision on VNLE output
|
||||
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
|
||||
|
||||
% Process through postfilter and MLSE
|
||||
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
|
||||
mlse_.DIR = pf_.coefficients;
|
||||
|
||||
constellation = [-3, -1, 1, 3];
|
||||
chatgpt_answer(mlse_sig_sd.signal, Symbols.signal,mlse_.DIR,constellation);
|
||||
|
||||
% mlse_sig_sd = mlse_.process(mlse_sig_sd,Symbols);
|
||||
% mlse_sig_hd = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
|
||||
@@ -1,6 +1,6 @@
|
||||
|
||||
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"rrcalpha",rcalpha);
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"rrcalpha",rcalpha);
|
||||
|
||||
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
|
||||
"fsym",fsym,"M",M,"order",19,"useprbs",1,...
|
||||
|
||||
@@ -32,7 +32,7 @@ wh.addStorage("dbenc_package");
|
||||
|
||||
% === RUN IT ===
|
||||
|
||||
% [results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "parallel", 'wh', wh, 'waitbar', true);
|
||||
[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "parallel", 'wh', wh, 'waitbar', true);
|
||||
% wh.getStoValue('ffe_package',0.005);
|
||||
% wh.getStoValue('mlse_package',0.005);
|
||||
|
||||
|
||||
116
projects/Job_Processing/run_offline_dsp_script.m
Normal file
116
projects/Job_Processing/run_offline_dsp_script.m
Normal file
@@ -0,0 +1,116 @@
|
||||
dsp_options.append_to_db = false;
|
||||
dsp_options.max_occurences = 1;
|
||||
dsp_options.mode = "load_run_id";
|
||||
experiment = "highspeed_2024";
|
||||
|
||||
if dsp_options.mode == "load_run_id"
|
||||
|
||||
dsp_options.load_file_path = [];
|
||||
if experiment == 'highspeed_2024'
|
||||
|
||||
dsp_options.database_path = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\silas_labor_newdsp_newstructure.db';
|
||||
dsp_options.storage_path = 'Z:\2024\sioe_labor\';
|
||||
db = DBHandler("pathToDB", [dsp_options.database_path], "type", "sqlite");
|
||||
|
||||
elseif 'mpi_ecoc_2025'
|
||||
|
||||
dsp_options.database_path = []; %sqlite im netzwerk
|
||||
dsp_options.storage_path = 'Z:\2025\ECOC Silas\ecoc_2025\';
|
||||
db = DBHandler("pathToDB", [dsp_options.database_path], "type", "mysql");
|
||||
|
||||
end
|
||||
|
||||
|
||||
elseif dsp_options.mode == "load_files"
|
||||
|
||||
dsp_options.load_file_path.tx_bits_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091513_PAM_4_R_112_bits.mat"';
|
||||
dsp_options.load_file_path.tx_symbols_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091513_PAM_4_R_112_symbols.mat"';
|
||||
dsp_options.load_file_path.rx_raw_path = "Z:\2025\ECOC Silas\ecoc_2025\mpi_opti_1000m_pam2 4 6 8\20250417_091525_PAM_4_R_112_rec01_rx_signal_raw.mat"';
|
||||
|
||||
elseif dsp_options.mode == "simulate"
|
||||
|
||||
error('Not yet implemented')
|
||||
|
||||
end
|
||||
|
||||
|
||||
%% === Define Database Filters ===
|
||||
|
||||
if experiment == 'highspeed_2024'
|
||||
|
||||
fp = QueryFilter();
|
||||
db = db.getDistinctValues;
|
||||
%fp.where('Runs', 'run_id','EQUALS', 3);
|
||||
fp.where('Runs', 'pam_level','EQUALS', 4);
|
||||
allrates = string(num2str(sort(db.distinctValues.Runs.bitrate.*1e-9)));
|
||||
fp.where('Runs', 'bitrate','EQUALS',390e9);
|
||||
alllengths = string(num2str(sort(db.distinctValues.Runs.fiber_length)));
|
||||
fp.where('Runs', 'fiber_length','EQUALS', 1);
|
||||
fp.where('Runs', 'is_mpi','EQUALS', 0);
|
||||
% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
|
||||
% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
|
||||
% fp.where('Runs', 'sir','EQUALS',18);
|
||||
fp.where('Runs', 'wavelength','EQUALS', 1310);
|
||||
fp.where('Runs', 'db_mode','EQUALS', 0);
|
||||
% fp.where('Runs', 'rop_attenuation','EQUALS', 0);
|
||||
fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
|
||||
|
||||
elseif experiment == 'mpi_ecoc_2025'
|
||||
|
||||
fp = QueryFilter();
|
||||
%fp.where('Runs', 'run_id','EQUALS', 3);
|
||||
fp.where('Runs', 'pam_level','EQUALS', 4);
|
||||
fp.where('Runs', 'bitrate','EQUALS',224e9);
|
||||
fp.where('Runs', 'is_mpi','EQUALS', 1);
|
||||
fp.where('Runs', 'interference_path_length','EQUALS', 1000);
|
||||
% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
|
||||
fp.where('Runs', 'sir','EQUALS',18);
|
||||
fp.where('Runs', 'wavelength','EQUALS', 1310);
|
||||
fp.where('Runs', 'db_mode','EQUALS', 0);
|
||||
% fp.where('Runs', 'rop_attenuation','EQUALS', 0);
|
||||
fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
|
||||
% fp.where('Runs', 'loop_id','EQUALS', 14);
|
||||
|
||||
end
|
||||
|
||||
|
||||
% === Queue from DB ===
|
||||
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
|
||||
|
||||
% === Adapt or filter Matlab Table ===
|
||||
% [~, unique_indices] = unique(dataTable.sir, 'first');
|
||||
% dataTable = dataTable(unique_indices, :);
|
||||
|
||||
|
||||
% === Set LOOPS & Initialize DataStorage ===
|
||||
dsp_options.parameters = struct();
|
||||
% dsp_options.parameters.adaption = [3];
|
||||
% dsp_options.parameters.mu_tr = 0.999;%[0,logspace(-4,0,10)];
|
||||
% dsp_options.parameters.mu_dd = [logspace(-0.004,0,20)];
|
||||
% dsp_options.parameters.use_dd_mode = [1];
|
||||
|
||||
wh = DataStorage(dsp_options.parameters);
|
||||
wh.addStorage("ffe_package");
|
||||
wh.addStorage("mlse_package");
|
||||
wh.addStorage("vnle_package");
|
||||
wh.addStorage("dbtgt_package");
|
||||
wh.addStorage("dbenc_package");
|
||||
|
||||
|
||||
% === RUN IT ===
|
||||
% run this function: dsp_runid(run_id, options)
|
||||
[results,wh] = submitJobs(dataTable.run_id, dsp_options, "serial", 'wh', wh, 'waitbar', false);
|
||||
|
||||
|
||||
%%
|
||||
BERs = cellfun(@(c) c.ffe_package{1,1}.metrics.BER, results);
|
||||
figure
|
||||
hold on
|
||||
plot(dsp_options.parameters.mu_dd,BERs,'Marker','+')
|
||||
yline([2.2e-4,4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
|
||||
set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
|
||||
xlabel('$\mu$ DD', 'Interpreter', 'latex');
|
||||
ylabel('BER', 'Interpreter', 'latex');
|
||||
legend('show', 'Location', 'best');
|
||||
grid on;
|
||||
hold off;
|
||||
Reference in New Issue
Block a user