Merge branch 'main' of cau-git.rz.uni-kiel.de:nt/mitarbeiter/silas/imdd_simulation
This commit is contained in:
sutef391
@@ -765,7 +765,7 @@ classdef Signal
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pkpos = sort(pkpos);
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if mean(w) > 10 || mean(p) > 10
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if mean(w) > 10 || mean(p) > 15
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return
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else
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sequenceFound = 1;
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@@ -15,6 +15,7 @@ classdef EML
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u_pi
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randomkey
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randomstream
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alpha
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%on instance creation
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field
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@@ -38,6 +39,7 @@ classdef EML
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options.lambda;
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options.power;
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options.linewidth = 0;
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options.alpha = 0;
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options.ampl_imbal = 0;
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options.pha_imbal = 0;
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options.bias;
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@@ -101,9 +103,21 @@ classdef EML
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end
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%modulate the laserfield with the electrical signal
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opt_out = obj.externalmodulation(laserfield,elec_in);
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laserfield = obj.externalmodulation(laserfield,elec_in);
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% add chirp
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opt_out = obj.chirp(laserfield);
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end
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function chirped_field = chirp(obj,laserfield)
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% Chirp
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p = abs(laserfield.^2);
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derv_p = [0; diff(p)];
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delta_phi = derv_p./(4*pi*p).*obj.alpha;
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delta_phi = cumsum(delta_phi);
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chirped_field = laserfield.*exp(1i*2*pi*delta_phi);
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end
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@@ -10,12 +10,12 @@ if 1
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uloops.laser_wavelength = [1310];
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uloops.M = [4];
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uloops.link_length = [1]; % 1,2,3,5,6,8,10
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uloops.interference_attenuation = [0,3,6,9,12,15,18,21,24,27,30,45];
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% uloops.interference_attenuation = [0,3,6,9,12,15,18,21,24,27,30,45];
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wh = DataStorage(uloops);
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wh.addStorage("ber");
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% wh = submit_simulations(wh,"parallel",0,"simulation_mode",0);
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wh = submit_handle(@imdd_model,wh,"parallel",0);
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wh = submit_handle(@imdd_model,wh,"serial",0);
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end
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@@ -137,8 +137,7 @@ end
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f_nyquist = fsym/2;
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%%% run the simulation or measurement or ...
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if simulation_mode
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Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
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rcalpha = 1;
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@@ -205,67 +204,6 @@ if simulation_mode
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Scpe_cell{1} = Scpe_sig;
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else
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profile on
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basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
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database = DBHandler("pathToDB",[basePath,'silas_labor.db']);
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profile off
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basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
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useGui = 0;
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% db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
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filterParams = database.tables;
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% filterParams.Runs.run_id = 2958; % no db
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% filterParams.Runs.run_id = 2937; % no db
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filterParams.Configurations = struct( ...
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'bitrate', bitrate, ...
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'db_mode', db_precode+db_encode, ...
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'fiber_length', link_length, ...
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'interference_attenuation', [], ...
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'interference_path_length', [], ...
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'is_mpi', is_mpi, ...
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'pam_level', M, ...
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'precomp_amp', [], ...
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'rop_attenuation', 0, ...
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'symbolrate', [], ...
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'v_awg', [], ...
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'v_bias', [], ...
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'wavelength', laser_wavelength ...
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);
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selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
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'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.symbolrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','Measurements.power_rop','Configurations.v_bias',...
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'Configurations.interference_attenuation'};
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[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
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[~, uniqueIdx] = unique(dataTable.run_id); % Get unique run_id indices
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dataTable = dataTable(uniqueIdx,:); % Extract unique configurations for each run_id
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fprintf('Found %d entries for requested Configuration. IDs are: %s \n \n',size(dataTable,1),jsonencode(dataTable.run_id(1:min(size(dataTable,1),100))));
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Tx_bits = load([basePath, char(dataTable.tx_bits_path(end))]);
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Tx_bits = Tx_bits.Bits;
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Symbols = load([basePath, char(dataTable.tx_symbols_path(end))]);
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Symbols = Symbols.Symbols;
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Scpe_load = load([basePath, char(dataTable.rx_sync_path(end))]);
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Scpe_cell = Scpe_load.S;
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% Raw_signal = load([basePath, char(dataTable.rx_raw_path(1))]);
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% Raw_signal.Scpe_sig_raw.plot("displayname",'0db atten','fignum',10101)
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% Raw_signal = Raw_signal.Scpe_sig_raw;
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%
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% Raw_signal = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.55,"fs",Raw_signal.fs,"filterType",filtertypes.gaussian,"active",true).process(Raw_signal);
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%
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% Scpe_cell{1}.eye(fsym,M,"displayname",'eye','fignum',227);
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%
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% Raw_signal.spectrum("normalizeTo0dB",0,"fignum",11,"fft_length",2^12);
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% Raw_signal.move_it_spectrum("fignum",334);
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% Raw_signal.move_it_spectrum("fignum",334);
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fsym = Symbols.fs;
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end
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if db_precode
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Symbols_precoded = Symbols;
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@@ -59,7 +59,7 @@ Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",1
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db_precode = 0;
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db_encode = 0;
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duob_mode = db_mode.db_precoded;
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duob_mode = db_mode.no_db;
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apply_pulsef = 1;
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[Digi_sig,Symbols,Tx_bits] = PAMsource(...
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"fsym",fsym,"M",M,"order",18,"useprbs",0,...
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@@ -72,13 +72,12 @@ apply_pulsef = 1;
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Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
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%% proof of concept
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Symbols_db = Duobinary().encode(Symbols);
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mim_decoded = Duobinary().decode(Symbols_db,"M",M);
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rx_bits_mim_decoded = PAMmapper(M,0,"eth_style",0).demap(mim_decoded);
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rx_bits_mim_decoded_.signal = circshift(rx_bits_mim_decoded.signal,0);
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[~,~,ber_mim_decode,~] = calc_ber(rx_bits_mim_decoded_.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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fprintf('BER mim: %.2e \n',ber_mim_decode);
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% %% proof of concept memoryless inverse mapping (direct db targeting and decoding)
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% Symbols_db = Duobinary().encode(Symbols);
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% mim_decoded = Duobinary().decode(Symbols_db,"M",M);
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% rx_bits_mim_decoded = PAMmapper(M,0,"eth_style",0).demap(mim_decoded);
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% [~,~,ber_mim_decode,~] = calc_ber(rx_bits_mim_decoded_.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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% fprintf('BER mim: %.2e \n',ber_mim_decode);
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%%
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@@ -1,207 +1,290 @@
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%% Robust eval/plot script for res.* (handles missing/partial dims)
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% res.ffe stored like: output_ffe{ch, rop, realiz, eval_distance}
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% BUT: some dimensions may be singleton or not fully filled (e.g. only 0 km, only 1 realization)
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%saved like this: output_ffe{ch,rop,realiz,eval_distance}
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% -------------------- Basic metadata --------------------
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rop = res.settings.rop(:);
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wavelengthplan = res.settings.wavelengthplan(:);
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distances = res.eval_dist_km(:); % can be [0], [2 10], etc.
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N_ch = numel(wavelengthplan);
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N_rop = numel(rop);
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% -------------------- Determine dims robustly --------------------
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% Ensure we have 4D addressing even if MATLAB collapses trailing singletons
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dims = size(res.ffe);
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rop = res.settings.rop;
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wavelengthplan = res.settings.wavelengthplan;
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N_distances = dims(4); %usually 2km and 10km are evaualted
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distances = res.eval_dist_km; %[2,10]
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N_ch = length(wavelengthplan); %16 channels
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figure(); hold on;
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cols = cbrewer2('set2',N_ch); % one color per wavelength (Ch)
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if numel(dims) < 4
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dims(end+1:4) = 1;
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end
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N_realiz = dims(3);
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N_distances = dims(4);
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fec = 2.2e-4;
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fec = 3.8e-3;
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Sffe = cell(1,N_ch);
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Svnle = cell(1,N_ch);
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Smlse = cell(1,N_ch);
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Sdbt = cell(1,N_ch);
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% If res.eval_dist_km length differs from dims(4), trust dims(4)
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if numel(distances) ~= N_distances
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% best-effort fallback
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distances = (1:N_distances).';
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end
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% Choose your quantile band. For your old style, use 0.04/0.99:
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qLow = 0.0; % lower quantile (e.g., 0.04 for old script)
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qHigh = 1; % upper quantile (e.g., 0.99 for old script)
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cols = linspecer(N_ch); % one color per wavelength (Ch)
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cols = cbrewer2('RdBu',N_ch);
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% -------------------- Plot settings --------------------
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fec = 3.8e-3; % choose one; you can switch to 2.2e-4 if needed
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qLow = 0.00;
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qHigh = 1.00;
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% Color per wavelength/channel
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try
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cols = ccbrewer2('Set1', N_ch);
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catch
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cols = linspecer(N_ch);
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end
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% Containers for FEC crossings per channel (per eval distance)
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Sffe = cell(N_distances, N_ch);
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Sdfe = cell(N_distances, N_ch);
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Svnle = cell(N_distances, N_ch);
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Smlse = cell(N_distances, N_ch);
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Sdbt = cell(N_distances, N_ch);
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% -------------------- Choose which eval distances to plot --------------------
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% If you want all: eval_list = 1:N_distances;
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% If you want a specific distance (e.g., last): eval_list = N_distances;
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eval_list = 1;%1:N_distances;
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% -------------------- BER vs ROP figures (one figure per eval distance) --------------------
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for eval_ptr = eval_list
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figure('Name', sprintf('BER vs ROP @ %s', distLabel(distances, eval_ptr)));
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hold on;
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for eval_ptr = 2
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for ch = 1:N_ch
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% Slice 12x50 cell arrays
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ffe_cells = reshape(squeeze(res.ffe(ch,:,:,eval_ptr)),length(rop),[]);
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vnle_cells = reshape(squeeze(res.vnle(ch,:,:,eval_ptr)),length(rop),[]);
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mlse_cells = reshape(squeeze(res.mlse(ch,:,:,eval_ptr)),length(rop),[]);
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dbt_cells = reshape(squeeze(res.dbt(ch,:,:,eval_ptr)),length(rop),[]);
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% ---- Extract cell slices robustly: [N_rop x N_realiz] ----
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ffe_cells = sliceCells4D(res.ffe , ch, eval_ptr, N_rop);
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dfe_cells = sliceCells4D(res.dfe , ch, eval_ptr, N_rop);
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vnle_cells = sliceCells4D(res.vnle, ch, eval_ptr, N_rop);
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mlse_cells = sliceCells4D(res.mlse, ch, eval_ptr, N_rop);
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dbt_cells = sliceCells4D(res.dbt , ch, eval_ptr, N_rop);
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[Sffe{ch}, noX_ffe] = fecCrossings(rop, ffe_cells, fec);
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% ---- FEC crossings (works with incomplete columns) ----
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[Sffe{eval_ptr,ch}, ~] = fecCrossings(rop, ffe_cells, fec);
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[Sdfe{eval_ptr,ch}, ~] = fecCrossings(rop, dfe_cells, fec);
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[Svnle{eval_ptr,ch}, ~] = fecCrossings(rop, vnle_cells, fec);
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[Smlse{eval_ptr,ch}, ~] = fecCrossings(rop, mlse_cells, fec);
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[Sdbt{eval_ptr,ch}, ~] = fecCrossings(rop, dbt_cells, fec);
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[Svnle{ch}, noX_ffe] = fecCrossings(rop, vnle_cells, fec);
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% ---- Extract BER matrices using only complete realizations ----
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ffe_mat = extractCompleteBER(ffe_cells); % N_rop x K
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dfe_mat = extractCompleteBER(dfe_cells);
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vnle_mat = extractCompleteBER(vnle_cells);
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mlse_mat = extractCompleteBER(mlse_cells);
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dbt_mat = extractCompleteBER(dbt_cells);
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[Smlse{ch}, noX_ffe] = fecCrossings(rop, mlse_cells, fec);
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showLegend = (ch == 1); % one legend entry per technique
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[Sdbt{ch}, noX_ffe] = fecCrossings(rop, dbt_cells, fec);
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% Plot bands + mean (only if non-empty)
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if ~isempty(ffe_mat)
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plotBandMeanBL(rop, ffe_mat, cols(ch,:), sprintf('FFE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--s', showLegend);
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end
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% if ~isempty(dfe_mat)
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% plotBandMeanBL(rop, dfe_mat, cols(ch,:), sprintf('DFE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
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% end
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% if ~isempty(vnle_mat)
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% plotBandMeanBL(rop, vnle_mat, cols(ch,:), sprintf('VNLE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--x', showLegend);
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% end
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% if ~isempty(mlse_mat)
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% plotBandMeanBL(rop, mlse_mat, cols(ch,:), sprintf('VNLE+PF+MLSE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
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% end
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% if ~isempty(dbt_mat)
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% plotBandMeanBL(rop, dbt_mat, cols(ch,:), sprintf('DBt+MLSE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--v', showLegend);
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% end
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% Extract BER matrices using only complete realizations (12/12 ROP filled)
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ffe_mat = extractCompleteBER(ffe_cells); % 12 x K_ffe
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vnle_mat = extractCompleteBER(vnle_cells); % 12 x K_vnle
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mlse_mat = extractCompleteBER(mlse_cells); % 12 x K_mlse
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mlse_alpha_mat = extractCompleteAlphas(mlse_cells); % 12 x K_mlse
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dbt_mat = extractCompleteBER(dbt_cells); % 12 x K_dbt
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showLegend = 1; % one legend entry per technique
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% Plot shaded band + mean line with boundedline
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% plotBandMeanBL(rop, ffe_mat, cols(ch,:), sprintf('FFE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--s', showLegend);
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% scatter(Sffe,fec.*ones(size(Sffe)),20,'v','MarkerFaceColor','black');
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% plotBandMeanBL(rop, vnle_mat, cols(ch,:), sprintf('VNLE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--x', showLegend);
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% plotBandMeanBL(rop, mlse_mat, cols(ch,:), sprintf('VNLE+PF+MLSE @ %.1d nm',round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
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||||
|
||||
% plotBandMeanBL(rop, dbt_mat, cols(ch,:), sprintf('DBt.+MLSE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--v', showLegend);
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end
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||||
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set(gca,'XScale','linear','YScale','log','TickLabelInterpreter','latex','FontSize',11);
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yline([3.8e-3, 2.2e-4], 'HandleVisibility','off','LineWidth',1.5);
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||||
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||||
end
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||||
end
|
||||
|
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ylabel('BER');
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xlabel('ROP');
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title('BER vs. ROP');
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xlabel('ROP [dB]');
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title(sprintf('BER vs. ROP @ %s', distLabel(distances, eval_ptr)));
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xlim([min(rop) max(rop)]);
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ylim([1e-5 0.3]);
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grid on;
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legend show;
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end
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||||
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||||
%% VIOLIN
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||||
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S_cell = Sdbt;
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S_cell = Smlse;
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S_cell = {Svnle,Smlse,Sdbt};
|
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S_cell = {Svnle};
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figure(5); hold on;
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for i = 1:length(S_cell)
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% Pad to rectangular matrix: rows = realizations, cols = wavelengths
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Kmax = max(cellfun(@numel, S_cell{i}));
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S_mat = NaN(Kmax, N_ch);
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%% -------------------- VIOLIN of ROP at FEC crossing --------------------
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% Build technique groups; each group is {N_distances x N_ch} cell entries
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% You can pick a distance to show (e.g., eval_ptr=1 for 0 km, or last)
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eval_ptr_violin = min(N_distances, max(1, N_distances)); % default: last available
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% eval_ptr_violin = 1;
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% Choose which technique(s) to show
|
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techNames = {'VNLE'};
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S_groups = {Svnle(eval_ptr_violin,:)};
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|
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% Only plot if violinplot exists
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if exist('violinplot','file') == 2
|
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figure('Name', sprintf('FEC crossing violin @ %s', distLabel(distances, eval_ptr_violin))); hold on;
|
||||
|
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colsTech = linspecer(numel(S_groups));
|
||||
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for i = 1:numel(S_groups)
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S_cell = S_groups{i}; % 1 x N_ch cell, each cell is 1xK crossings
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||||
|
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% Pad to rectangular: rows = realizations (max K), cols = wavelengths (N_ch)
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Kmax = max(cellfun(@numel, S_cell));
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if isempty(Kmax) || Kmax == 0
|
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continue;
|
||||
end
|
||||
S_mat = zeros(Kmax, N_ch);
|
||||
for ch = 1:N_ch
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k = numel(S_cell{i}{ch});
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||||
k = numel(S_cell{ch});
|
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if k > 0
|
||||
S_mat(1:k, ch) = S_cell{i}{ch};
|
||||
S_mat(1:k, ch) = S_cell{ch}(:);
|
||||
end
|
||||
end
|
||||
|
||||
% --- Violin plot over wavelengths (columns) ---
|
||||
|
||||
cols=linspecer(3);
|
||||
catLabels = arrayfun(@(nm) sprintf('%d nm', nm), wavelengthplan, 'UniformOutput', false);
|
||||
vs = violinplot(S_mat, catLabels, ...
|
||||
'ViolinColor', cols(i,:), ...
|
||||
catLabels = arrayfun(@(nm) sprintf('%d nm', nm), round(wavelengthplan), 'UniformOutput', false);
|
||||
violinplot(S_mat, catLabels, ...
|
||||
'ViolinColor', colsTech(i,:), ...
|
||||
'ViolinAlpha', 0.10, ...
|
||||
'MarkerSize', 20, ...
|
||||
'ShowMedian', true, ...
|
||||
'EdgeColor', cols(i,:), ...
|
||||
'EdgeColor', colsTech(i,:), ...
|
||||
'ShowWhiskers', false, ...
|
||||
'ShowData', true, ...
|
||||
'ShowBox', false, ...
|
||||
'Bandwidth', 0.05);
|
||||
|
||||
ylim([floor(min(S_mat,[],'all')), ceil(max(S_mat,[],'all'))])
|
||||
% ylim([-8 0]);
|
||||
ylabel('ROP at FEC crossing');
|
||||
title(sprintf('RROP to cross BER %.2e', fec));
|
||||
grid on; box on;
|
||||
% Add a legend proxy
|
||||
plot(nan, nan, 'o', 'Color', colsTech(i,:), 'DisplayName', techNames{i});
|
||||
end
|
||||
|
||||
ylim([-10,-6])
|
||||
ylabel('ROP at FEC crossing');
|
||||
title(sprintf('ROP to cross BER %.2e @ %s', fec, distLabel(distances, eval_ptr_violin)));
|
||||
grid on; box on;
|
||||
legend show;
|
||||
else
|
||||
fprintf('violinplot.m not found on path -> skipping violin plot.\n');
|
||||
end
|
||||
|
||||
|
||||
%% ================= helper =================
|
||||
%% ================= helpers =================
|
||||
|
||||
function cells2D = sliceCells4D(C4, ch, eval_ptr, N_rop)
|
||||
% Returns a [N_rop x N_realiz] cell array (with N_realiz inferred)
|
||||
% Works even if trailing dimensions are singleton.
|
||||
%
|
||||
% If C4 is smaller than expected, missing entries are returned as [].
|
||||
|
||||
dims = size(C4);
|
||||
if numel(dims) < 4, dims(end+1:4) = 1; end
|
||||
N_realiz = dims(3);
|
||||
|
||||
cells2D = cell(N_rop, N_realiz);
|
||||
|
||||
% bounds (in case stored arrays are smaller)
|
||||
chMax = dims(1);
|
||||
ropMax = dims(2);
|
||||
rMax = dims(3);
|
||||
eMax = dims(4);
|
||||
|
||||
if ch > chMax || eval_ptr > eMax
|
||||
return; % all empty
|
||||
end
|
||||
|
||||
ropUse = min(N_rop, ropMax);
|
||||
rUse = min(N_realiz, rMax);
|
||||
|
||||
% Extract and place into a consistent sized cell matrix
|
||||
tmp = squeeze(C4(ch, 1:ropUse, 1:rUse, eval_ptr));
|
||||
% squeeze may return vector/empty if rUse==1 etc. Normalize:
|
||||
tmp = reshape(tmp, ropUse, rUse);
|
||||
|
||||
cells2D(1:ropUse, 1:rUse) = tmp;
|
||||
end
|
||||
|
||||
function lbl = distLabel(distances, eval_ptr)
|
||||
if eval_ptr <= numel(distances)
|
||||
d = distances(eval_ptr);
|
||||
if isfinite(d)
|
||||
lbl = sprintf('%.0f km', d);
|
||||
return;
|
||||
end
|
||||
end
|
||||
lbl = sprintf('eval\\_%d', eval_ptr);
|
||||
end
|
||||
|
||||
function plotBandMeanBL(x, Y, color, techLabel, qLow, qHigh, lineSpec, showLegend)
|
||||
% Y: (nPoints x nRealizations)
|
||||
% Remove realizations that are entirely zero (like removeZeros behavior)
|
||||
if isempty(Y), return; end
|
||||
|
||||
% Remove realizations that are entirely zero
|
||||
badCols = all(Y == 0, 1);
|
||||
Y(:, badCols) = [];
|
||||
|
||||
Y(Y==0) = 1e-8;
|
||||
% Stats across realizations
|
||||
mu = mean(Y, 2, 'omitnan'); % mean line
|
||||
lo = quantile(Y, qLow, 2); % lower bound
|
||||
hi = quantile(Y, qHigh, 2); % upper bound
|
||||
if isempty(Y), return; end
|
||||
|
||||
% Convert to asymmetric distances required by boundedline:
|
||||
% b(:,1) = distance to lower side; b(:,2) = distance to upper side
|
||||
% Avoid log(0)
|
||||
Y(Y==0) = 1e-8;
|
||||
|
||||
mu = mean(Y, 2, 'omitnan');
|
||||
lo = quantile(Y, qLow, 2);
|
||||
hi = quantile(Y, qHigh, 2);
|
||||
b = [mu - lo, hi - mu];
|
||||
|
||||
% Call boundedline with alpha shading
|
||||
[hl, hp] = boundedline(x(:), mu(:), b, lineSpec, 'alpha', ...
|
||||
'transparency', 0.18);
|
||||
% Color styling
|
||||
% boundedline optional; fallback to simple plot if missing
|
||||
if 0%exist('boundedline','file') == 2
|
||||
[hl, hp] = boundedline(x(:), mu(:), b, lineSpec, 'alpha', 'transparency', 0.18);
|
||||
set(hl, 'Color', color, 'LineWidth', 1.4, 'MarkerSize', 4);
|
||||
set(hp, 'FaceColor', color, 'HandleVisibility','off'); % patch hidden in legend
|
||||
set(hp, 'FaceColor', color, 'HandleVisibility','off');
|
||||
else
|
||||
hl = plot(x(:), mu(:), lineSpec, 'LineWidth', 1.4, 'MarkerSize', 4);
|
||||
set(hl, 'Color', color);
|
||||
end
|
||||
|
||||
% Single legend entry per technique (use first wavelength only)
|
||||
if showLegend
|
||||
set(hl, 'DisplayName', techLabel);
|
||||
else
|
||||
set(hl, 'HandleVisibility','off');
|
||||
end
|
||||
|
||||
% Optional: outline the bounds if outlinebounds is available
|
||||
if exist('outlinebounds','file') == 2
|
||||
if 0%exist('outlinebounds','file') == 2 && exist('boundedline','file') == 2
|
||||
ho = outlinebounds(hl, hp);
|
||||
set(ho, 'linestyle', ':', 'color', color, 'linewidth', 1, ...
|
||||
'HandleVisibility','off');
|
||||
set(ho, 'linestyle', ':', 'color', color, 'linewidth', 1, 'HandleVisibility','off');
|
||||
end
|
||||
end
|
||||
|
||||
function [S, noCrossingMask, Y_keep] = fecCrossings(rop, cells12xR, fec)
|
||||
% cells12xR: 12xR cell array (one wavelength + scheme slice)
|
||||
% each cell must be a struct with .metrics.BER
|
||||
% rop: 12x1 numeric vector of ROP points
|
||||
% fec: scalar FEC threshold (e.g., 3.8e-3)
|
||||
%
|
||||
% Outputs:
|
||||
% S 1xK vector of crossing ROP per kept realization (NaN if none)
|
||||
% noCrossingMask 1xK logical mask: true if no crossing for that realization
|
||||
% Y_keep 12xK numeric BER matrix used for the crossing detection
|
||||
|
||||
% 1) keep only complete realization columns
|
||||
Y = extractCompleteBER(cells12xR); % -> 12 x K
|
||||
function [S, noCrossingMask] = fecCrossings(rop, cellsNxR, fec)
|
||||
% cellsNxR: N_rop x R cell array; each cell is struct with .metrics.BER
|
||||
Y = extractCompleteBER(cellsNxR); % -> N_rop x K
|
||||
if isempty(Y)
|
||||
S = [];
|
||||
noCrossingMask = [];
|
||||
Y_keep = Y;
|
||||
return;
|
||||
end
|
||||
|
||||
% 2) optionally drop realizations with mean BER > 0.1
|
||||
ok = mean(Y,1,'omitnan') <= 0.1;
|
||||
Y = Y(:, ok);
|
||||
if isempty(Y)
|
||||
S = [];
|
||||
noCrossingMask = [];
|
||||
Y_keep = Y;
|
||||
return;
|
||||
end
|
||||
|
||||
% 3) find crossings per realization
|
||||
nR = size(Y,2);
|
||||
S = nan(1,nR);
|
||||
noCrossingMask = true(1,nR);
|
||||
|
||||
rop = rop(:); % ensure column
|
||||
rop = rop(:);
|
||||
for j = 1:nR
|
||||
y = Y(:,j);
|
||||
|
||||
% sign change from >fec to <=fec (first time it drops below FEC)
|
||||
above = (y > fec);
|
||||
idx = find(above(1:end-1) & ~above(2:end), 1, 'first');
|
||||
|
||||
if ~isempty(idx)
|
||||
% linear interpolation between (x1,y1) and (x2,y2)
|
||||
x1 = rop(idx); y1 = y(idx);
|
||||
x2 = rop(idx+1); y2 = y(idx+1);
|
||||
|
||||
if isfinite(y1) && isfinite(y2) && y2 ~= y1
|
||||
t = (fec - y1) / (y2 - y1);
|
||||
S(j) = x1 + t*(x2 - x1);
|
||||
@@ -209,37 +292,34 @@ for j = 1:nR
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
Y_keep = Y;
|
||||
end
|
||||
|
||||
|
||||
|
||||
function Y = extractCompleteBER(cellSlice)
|
||||
% cellSlice: 12xR cell array; each cell should be a struct with .metrics.BER
|
||||
% Keep only those realization columns where ALL 12 ROP entries are valid.
|
||||
% Keep only those realization columns where ALL N_rop entries are non-empty
|
||||
if isempty(cellSlice), Y = []; return; end
|
||||
nR = size(cellSlice,2);
|
||||
keep = false(1,nR);
|
||||
|
||||
for r = 1:nR
|
||||
col = cellSlice(:,r);
|
||||
keep(r) = all(cellfun(@(c) ~isempty(c), col));
|
||||
end
|
||||
|
||||
if ~any(keep), Y = []; return; end
|
||||
|
||||
Y = cellfun(@(c) c.metrics.BER, cellSlice(:,keep), 'UniformOutput', true);
|
||||
end
|
||||
|
||||
function Y = extractCompleteAlphas(cellSlice)
|
||||
% cellSlice: 12xR cell array; each cell should be a struct with .metrics.BER
|
||||
% Keep only those realization columns where ALL 12 ROP entries are valid.
|
||||
if isempty(cellSlice), Y = []; return; end
|
||||
nR = size(cellSlice,2);
|
||||
keep = false(1,nR);
|
||||
|
||||
for r = 1:nR
|
||||
col = cellSlice(:,r);
|
||||
keep(r) = all(cellfun(@(c) ~isempty(c), col));
|
||||
end
|
||||
|
||||
if ~any(keep), Y = []; return; end
|
||||
Y = cellfun(@(c) c.metrics.Alpha, cellSlice(:,keep), 'UniformOutput', true);
|
||||
end
|
||||
|
||||
|
||||
@@ -67,8 +67,8 @@ fname = sprintf('WDM_%s_%s_%s_%dkm_%dch_%dghz_%s.mat', char(t), host, jobid, opt
|
||||
s.num_realiz = options.num_realiz;
|
||||
s.wavelengthplan = calcWavelengthPlan(options.num_channels, options.channel_spacing, 1310);
|
||||
link_length = options.fiber_length_km;
|
||||
s.pmd = 0.1;
|
||||
s.gamma = 0.0023;
|
||||
s.pmd = 0;%0.1;
|
||||
s.gamma = 0;%0.0023;
|
||||
|
||||
s.M = 4;
|
||||
fsym = 112e9;
|
||||
@@ -108,7 +108,7 @@ Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",1
|
||||
|
||||
N = numel(s.wavelengthplan);
|
||||
f_plan = physconst('lightspeed')./(s.wavelengthplan.*1e-9);
|
||||
margin = 20e12; % some THz left and right
|
||||
margin = 2e12; % some THz left and right
|
||||
f_span = (max(f_plan)+margin)-(min(f_plan)-margin);
|
||||
f_nyq = f_span/2;
|
||||
|
||||
@@ -124,13 +124,13 @@ signal_cell = {};
|
||||
Symbols = {};
|
||||
Tx_bits = {};
|
||||
|
||||
s.rop = -12:0.75:-0.75;
|
||||
s.rop = -12;%:0.75:-0;
|
||||
|
||||
%% ---------- Intermediate evaluation points (distance dimension) ----------
|
||||
% Evaluate BER at these intermediate distances (km), plus always include the final link_length if > 0.
|
||||
segment_length = 1; % km (must match fiber loop below)
|
||||
|
||||
eval_dist_km = [2 10];
|
||||
eval_dist_km = [10];
|
||||
eval_dist_km = eval_dist_km(eval_dist_km <= link_length);
|
||||
|
||||
% Always include final distance (if > 0) and avoid duplicates
|
||||
@@ -209,7 +209,7 @@ for realiz = 1:s.num_realiz
|
||||
% E/O Conversion
|
||||
Eml_out = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs, ...
|
||||
"lambda",s.wavelengthplan(l),"bias",vbias,"u_pi",u_pi, ...
|
||||
"linewidth",laser_linewidth,"randomkey",s.random_key+l+realiz).process(El_sig);
|
||||
"linewidth",laser_linewidth,"randomkey",s.random_key+l+realiz,"alpha",0.8).process(El_sig);
|
||||
|
||||
signal_cell{l} = Polarization_Controller("mode","rot_power","desired_power",pol_rot(l)).process(Eml_out);
|
||||
end
|
||||
|
||||
@@ -1,18 +1,14 @@
|
||||
function WDM_model_10km_queue(options)
|
||||
%WDM_model_10km_queue
|
||||
% Job-queue / pipeline version of your script:
|
||||
% - Main thread runs fiber propagation segment-by-segment
|
||||
% - At each eval distance: demux once and enqueue per-(l,ri) DSP jobs via parfeval
|
||||
% - While continuing propagation: periodically harvest completed jobs (non-blocking)
|
||||
% - End of realization: drain remaining jobs, then save
|
||||
%
|
||||
% Save this as a NEW file, e.g. "WDM_model_10km_queue.m"
|
||||
%WDM_model_10km_queue_memopt
|
||||
% Queue/pipeline version with:
|
||||
% (a) reduced variable lifetime / fewer unnecessary copies (clear large temporaries early)
|
||||
% (b) worker-side memory monitoring (RSS logging to per-worker files)
|
||||
|
||||
%%% Run parameters
|
||||
arguments
|
||||
options.num_channels = 16;
|
||||
options.channel_spacing = 400e9;
|
||||
options.fiber_length_km = 2;
|
||||
options.fiber_length_km = 10;
|
||||
options.rand_key = 1;
|
||||
options.num_realiz = 1;
|
||||
options.fwm_mitigation_technique = "co";
|
||||
@@ -65,12 +61,16 @@ if ~exist(output_root,'dir'), mkdir(output_root); end
|
||||
|
||||
fname = sprintf('WDM_%s_%s_%s_%dkm_%dch_%dghz_%s.mat', char(t), host, jobid, options.fiber_length_km(end), options.num_channels, options.channel_spacing.*1e-9, options.fwm_mitigation_technique);
|
||||
|
||||
% Worker memory logs directory
|
||||
memlog_dir = fullfile(output_root, 'memlogs');
|
||||
if ~exist(memlog_dir,'dir'), mkdir(memlog_dir); end
|
||||
|
||||
%% Settings
|
||||
s.num_realiz = options.num_realiz;
|
||||
s.wavelengthplan = calcWavelengthPlan(options.num_channels, options.channel_spacing, 1310);
|
||||
link_length = options.fiber_length_km;
|
||||
s.pmd = 0.1;
|
||||
s.gamma = 0.0023;
|
||||
s.pmd = 0;%0.1;
|
||||
s.gamma = 0;%0.0023;
|
||||
|
||||
s.M = 4;
|
||||
fsym = 112e9;
|
||||
@@ -105,7 +105,7 @@ Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",1
|
||||
|
||||
N = numel(s.wavelengthplan);
|
||||
f_plan = physconst('lightspeed')./(s.wavelengthplan.*1e-9);
|
||||
margin = 25e12; % some THz left and right
|
||||
margin = 2e12; % some THz left and right
|
||||
f_span = (max(f_plan)+margin)-(min(f_plan)-margin);
|
||||
f_nyq = f_span/2;
|
||||
|
||||
@@ -117,11 +117,11 @@ s.f_opt = fdac*kover*upsample_pow;
|
||||
s.f_opt_nyq = s.f_opt/2;
|
||||
|
||||
s.rop = -12:0.75:-0.75;
|
||||
|
||||
% s.rop = -12:1:0;
|
||||
%% ---------- Intermediate evaluation points (distance dimension) ----------
|
||||
segment_length = 1; % km (must match fiber loop below)
|
||||
|
||||
eval_dist_km = [2 10];
|
||||
eval_dist_km = [0];
|
||||
eval_dist_km = eval_dist_km(eval_dist_km <= link_length);
|
||||
|
||||
if link_length > 0
|
||||
@@ -167,7 +167,7 @@ end
|
||||
|
||||
for realiz = 1:s.num_realiz
|
||||
|
||||
% Per-realization TX storage
|
||||
% Per-realization TX storage (needed later for DSP: Symbols/Tx_bits)
|
||||
signal_cell = cell(1,N);
|
||||
Symbols = cell(1,N);
|
||||
Tx_bits = cell(1,N);
|
||||
@@ -181,7 +181,7 @@ for realiz = 1:s.num_realiz
|
||||
for l = 1:N
|
||||
|
||||
[Digi_sig,Symbols{l},Tx_bits{l}] = PAMsource( ...
|
||||
"fsym",fsym,"M",s.M,"order",18,"useprbs",0, ...
|
||||
"fsym",fsym,"M",s.M,"order",17,"useprbs",0, ...
|
||||
"fs_out",fdac, ...
|
||||
"applyclipping",0,"clipfactor",1.5, ...
|
||||
"applypulseform",apply_pulsef,"pulseformer",Pform, ...
|
||||
@@ -192,31 +192,51 @@ for realiz = 1:s.num_realiz
|
||||
|
||||
Lp_awg = Filter('filtdegree',3,"f_cutoff",56e9,"fs",fdac*kover, ...
|
||||
"filterType",filtertypes.gaussian,"active",true);
|
||||
|
||||
El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover, ...
|
||||
"bit_resolution",6,"upsampling_method","samplehold","precomp_sinc_rolloff",0, ...
|
||||
"H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig);
|
||||
|
||||
% Digi_sig not needed after AWG
|
||||
clear Digi_sig
|
||||
|
||||
% Electrical Driver Amplifier
|
||||
El_sig = El_sig.normalize("mode","oneone");
|
||||
scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2));
|
||||
El_sig = El_sig .* scaling;
|
||||
|
||||
% E/O Conversion
|
||||
Eml_out = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs, ...
|
||||
"lambda",s.wavelengthplan(l),"bias",vbias,"u_pi",u_pi, ...
|
||||
"linewidth",laser_linewidth,"randomkey",s.random_key+l+realiz).process(El_sig);
|
||||
"linewidth",laser_linewidth,"randomkey",s.random_key+l+realiz,"alpha",0.8).process(El_sig);
|
||||
|
||||
% El_sig not needed after EML
|
||||
clear El_sig
|
||||
|
||||
signal_cell{l} = Polarization_Controller("mode","rot_power","desired_power",pol_rot(l)).process(Eml_out);
|
||||
|
||||
% Eml_out not needed after pol controller
|
||||
clear Eml_out Lp_awg
|
||||
end
|
||||
|
||||
disp('Signal generated for all channels.');
|
||||
|
||||
%% ---------- WDM mux + launch ----------
|
||||
Opt_sig_wdm = Optical_Multiplex("fs_in",fdac*kover,"fs_out",upsample_pow*fdac*kover, ...
|
||||
"lambda_center",1310,"random_key",0,"filtype",1,"B",120e9).process(signal_cell);
|
||||
|
||||
% IMPORTANT: signal_cell is not needed anymore after multiplex (Symbols/Tx_bits remain)
|
||||
clear signal_cell
|
||||
|
||||
Opt_sig_wdm = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power", ...
|
||||
"amplification_db",s.p_launch+10*log10(N)).process(Opt_sig_wdm);
|
||||
|
||||
%% ---------- Fiber propagation ----------
|
||||
Opt_sig_wdm_fib = Opt_sig_wdm;
|
||||
|
||||
% Opt_sig_wdm no longer needed as separate handle/object
|
||||
clear Opt_sig_wdm
|
||||
|
||||
nSegments = link_length/segment_length;
|
||||
if abs(nSegments - round(nSegments)) > 1e-12
|
||||
error('fiber_length_km=%g must be an integer multiple of segment_length=%g km.', link_length, segment_length);
|
||||
@@ -225,20 +245,70 @@ for realiz = 1:s.num_realiz
|
||||
|
||||
zdw = 1310;
|
||||
randomize_D = true;
|
||||
|
||||
% Guard for 0 km: avoid calling getDispersionVector(0,...) if it doesn't support it
|
||||
if nSegments > 0
|
||||
Dvec = getDispersionVector(nSegments, d_local, zdw, randomize_D, s.random_key+realiz);
|
||||
else
|
||||
Dvec = [];
|
||||
end
|
||||
|
||||
eval_ptr = 1;
|
||||
% =================== Queue throttle (prevents OOM) ===================
|
||||
% Limit how many futures can be outstanding (running + queued + finished-not-yet-fetched).
|
||||
% Start conservatively; you can raise to 4*NumWorkers if stable.
|
||||
maxInFlight = max(2, p.NumWorkers);
|
||||
% =====================================================================
|
||||
|
||||
% -------- Evaluate at 0 km (BTB) if requested --------
|
||||
if eval_ptr <= nEval && eval_seg(eval_ptr) == 0
|
||||
disp('0 km before demux.');
|
||||
Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1, ...
|
||||
"fs_out",fdac*kover,"fs_in",fdac*kover*upsample_pow,"lambda_center",1310).process(Opt_sig_wdm_fib);
|
||||
|
||||
cnt = 0;
|
||||
total = length(s.rop)*N;
|
||||
fprintf('total of %d jobs to enqueue at 0 km\n', total);
|
||||
|
||||
for ri = 1:length(s.rop)
|
||||
for l = 1:N
|
||||
cnt = cnt + 1;
|
||||
|
||||
% ---- Throttle before enqueueing more futures ----
|
||||
[F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt] = ...
|
||||
throttle_inflight(F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt, maxInFlight);
|
||||
|
||||
% Enqueue one job per (l,ri)
|
||||
F(end+1,1) = parfeval(p, @rx_job, 5, ...
|
||||
Opt_sig_wdm_demux{l}, ...
|
||||
s.rop(ri), ...
|
||||
Symbols{l}, Tx_bits{l}, ...
|
||||
s, l, ri, realiz, eval_ptr, ...
|
||||
fdac, kover, fadc, fsym, ...
|
||||
len_tr, mu_dc, mu_ffe, mu_dfe, dfe_order, duob_mode, ...
|
||||
memlog_dir);
|
||||
|
||||
fprintf('Enqueued job %d/%d for realiz %d/%d, l=%d/%d, ri=%d/%d at 0 km (inflight=%d/%d)\n', ...
|
||||
cnt, total, realiz, s.num_realiz, l, N, ri, length(s.rop), numel(F), maxInFlight);
|
||||
|
||||
meta(end+1) = struct('l',l,'ri',ri,'realiz',realiz,'eval_ptr',eval_ptr);
|
||||
end
|
||||
end
|
||||
|
||||
clear Opt_sig_wdm_demux
|
||||
eval_ptr = eval_ptr + 1;
|
||||
end
|
||||
% -----------------------------------------------------
|
||||
|
||||
|
||||
for seg = 1:nSegments
|
||||
|
||||
fprintf('Realiz %d/%d: Segment %d/%d \n', realiz, s.num_realiz, seg, nSegments);
|
||||
|
||||
if 1
|
||||
Opt_sig_wdm_fib = DP_Fiber("L",segment_length,"D",Dvec(seg),"Dpmd",s.pmd,"Ds",0.07, ...
|
||||
"beat_len",10,"corr_len",100,"dz",1,"manakov",0, ...
|
||||
"gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01, ...
|
||||
"SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1).process(Opt_sig_wdm_fib);
|
||||
end
|
||||
|
||||
% -------- Evaluate at intermediate distance (enqueue jobs) --------
|
||||
if eval_ptr <= nEval && seg == eval_seg(eval_ptr)
|
||||
@@ -246,39 +316,52 @@ for realiz = 1:s.num_realiz
|
||||
Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1, ...
|
||||
"fs_out",fdac*kover,"fs_in",fdac*kover*upsample_pow,"lambda_center",1310).process(Opt_sig_wdm_fib);
|
||||
|
||||
cnt = 0;
|
||||
total = length(s.rop)*N;
|
||||
fprintf('total of %d jobs to enqueue at 0 km\n', total);
|
||||
|
||||
for ri = 1:length(s.rop)
|
||||
for l = 1:N
|
||||
% Enqueue one job per (l,ri)
|
||||
|
||||
cnt = cnt + 1;
|
||||
|
||||
% ---- Throttle before enqueueing more futures ----
|
||||
[F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt] = ...
|
||||
throttle_inflight(F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt, maxInFlight);
|
||||
|
||||
F(end+1,1) = parfeval(p, @rx_job, 5, ...
|
||||
Opt_sig_wdm_demux{l}, ... % channel signal at this eval point
|
||||
s.rop(ri), ... % rop [dB]
|
||||
Symbols{l}, Tx_bits{l}, ...% reference + bits
|
||||
s, l, realiz, ... % settings + indices
|
||||
Opt_sig_wdm_demux{l}, ...
|
||||
s.rop(ri), ...
|
||||
Symbols{l}, Tx_bits{l}, ...
|
||||
s, l, ri, realiz, eval_ptr, ...
|
||||
fdac, kover, fadc, fsym, ...
|
||||
len_tr, mu_dc, mu_ffe, mu_dfe, dfe_order, duob_mode);
|
||||
len_tr, mu_dc, mu_ffe, mu_dfe, dfe_order, duob_mode, ...
|
||||
memlog_dir);
|
||||
|
||||
fprintf('Enqueued job %d/%d for realiz %d/%d, l=%d/%d, ri=%d/%d at 0 km (inflight=%d/%d)\n', ...
|
||||
cnt, total, realiz, s.num_realiz, l, N, ri, length(s.rop), numel(F), maxInFlight);
|
||||
|
||||
meta(end+1) = struct('l',l,'ri',ri,'realiz',realiz,'eval_ptr',eval_ptr);
|
||||
end
|
||||
end
|
||||
|
||||
clear Opt_sig_wdm_demux
|
||||
eval_ptr = eval_ptr + 1;
|
||||
end
|
||||
% ----------------------------------------------------------------
|
||||
|
||||
% Non-blocking harvest: store finished jobs (if any) while we continue propagation
|
||||
% Non-blocking harvest (your existing line)
|
||||
[F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt] = ...
|
||||
collect_done(F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt, false);
|
||||
|
||||
end
|
||||
|
||||
% Drain remaining jobs for this realization (blocking until queue is empty)
|
||||
while ~isempty(F)
|
||||
[F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt] = ...
|
||||
collect_done(F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt, true);
|
||||
end
|
||||
|
||||
%% Save results (per realization)
|
||||
|
||||
res = struct();
|
||||
res.settings = s;
|
||||
res.eval_dist_km = eval_dist_km;
|
||||
@@ -292,6 +375,9 @@ for realiz = 1:s.num_realiz
|
||||
fprintf('Saved results to: %s\n', fullfile(output_root, fname));
|
||||
disp(datetime('now','TimeZone','local','Format','yyyyMs.Mdd_HHmmss'));
|
||||
|
||||
% Per-realization large arrays that are no longer needed
|
||||
clear Opt_sig_wdm_fib Symbols Tx_bits Dvec
|
||||
|
||||
end
|
||||
|
||||
end % end main
|
||||
@@ -300,25 +386,39 @@ end % end main
|
||||
%% ========================= Local functions =========================
|
||||
|
||||
function [ffe_results, dfe_results, vnle_results, mlse_results, dbt_results] = rx_job( ...
|
||||
Opt_sig_chan, rop_db, Symbols_l, Tx_bits_l, s, l, realiz, ...
|
||||
fdac, kover, fadc, fsym, len_tr, mu_dc, mu_ffe, mu_dfe, dfe_order, duob_mode)
|
||||
Opt_sig_chan, rop_db, Symbols_l, Tx_bits_l, s, l, ri, realiz, eval_ptr, ...
|
||||
fdac, kover, fadc, fsym, len_tr, mu_dc, mu_ffe, mu_dfe, dfe_order, duob_mode, memlog_dir)
|
||||
|
||||
% NOTE: keep plotting OFF in workers
|
||||
debug_plots = 0;
|
||||
|
||||
% Create per-worker logfile (avoid contention)
|
||||
logfile = make_worker_logfile(memlog_dir);
|
||||
|
||||
log_mem(logfile, 'job_start', l, ri, realiz, eval_ptr, rop_db, Opt_sig_chan);
|
||||
|
||||
%%%%%% ROP %%%%%%
|
||||
Opt_sig_wdm_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power", ...
|
||||
"amplification_db", rop_db).process(Opt_sig_chan);
|
||||
|
||||
% Opt_sig_chan no longer needed after amp
|
||||
clear Opt_sig_chan
|
||||
log_mem(logfile, 'after_amp', l, ri, realiz, eval_ptr, rop_db, Opt_sig_wdm_rx);
|
||||
|
||||
%%%%%% PD Square Law %%%%%%
|
||||
assert(fdac*kover==Opt_sig_wdm_rx.fs,'Sampling Frequencies do not match! Check previous steps');
|
||||
PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20, ...
|
||||
"nep",1.8e-11,"randomkey",s.random_key + l + realiz).process(Opt_sig_wdm_rx);
|
||||
|
||||
% Opt_sig_wdm_rx not needed after PD
|
||||
clear Opt_sig_wdm_rx
|
||||
log_mem(logfile, 'after_pd', l, ri, realiz, eval_ptr, rop_db, PD_sig);
|
||||
|
||||
%%%%%% Low-pass RX (PD, El. Connectors and Scope) %%%%%%
|
||||
rx_bwl = 100e9;
|
||||
PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover, ...
|
||||
"filterType",filtertypes.butterworth,"active",true).process(PD_sig);
|
||||
log_mem(logfile, 'after_rx_lpf', l, ri, realiz, eval_ptr, rop_db, PD_sig);
|
||||
|
||||
%%%%%% Low-pass Scope %%%%%%
|
||||
Lp_scpe = Filter('filtdegree',4,"f_cutoff",80e9,"fs",fadc, ...
|
||||
@@ -330,11 +430,28 @@ Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc, ...
|
||||
"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0, ...
|
||||
"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',0,'H_lpf',Lp_scpe).process(PD_sig);
|
||||
|
||||
% PD_sig no longer needed after scope
|
||||
clear PD_sig Lp_scpe
|
||||
log_mem(logfile, 'after_scope', l, ri, realiz, eval_ptr, rop_db, Scpe_sig);
|
||||
|
||||
Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym);
|
||||
|
||||
% Scpe_sig no longer needed after resample
|
||||
clear Scpe_sig
|
||||
log_mem(logfile, 'after_resample', l, ri, realiz, eval_ptr, rop_db, Scpe_sig_2sps);
|
||||
|
||||
[~, Scpe_cell, ~, ~] = Scpe_sig_2sps.tsynch("reference", Symbols_l, "fs_ref", fsym, "debug_plots", debug_plots);
|
||||
|
||||
% Scpe_sig_2sps no longer needed after sync
|
||||
clear Scpe_sig_2sps
|
||||
log_mem(logfile, 'after_sync', l, ri, realiz, eval_ptr, rop_db);
|
||||
|
||||
Rx_sig = Scpe_cell{1}.normalize("mode","rms");
|
||||
|
||||
% Scpe_cell no longer needed
|
||||
clear Scpe_cell
|
||||
log_mem(logfile, 'after_rxsig', l, ri, realiz, eval_ptr, rop_db, Rx_sig);
|
||||
|
||||
% -------------------- FFE --------------------
|
||||
ffe_order = [50, 0, 0];
|
||||
eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0], ...
|
||||
@@ -345,10 +462,11 @@ eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0], ...
|
||||
ffe_results = ffe(eq_ffe,s.M,Rx_sig,Symbols_l,Tx_bits_l, ...
|
||||
"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
|
||||
"eth_style_symbol_mapping",0);
|
||||
clear eq_ffe
|
||||
log_mem(logfile, 'after_ffe', l, ri, realiz, eval_ptr, rop_db);
|
||||
|
||||
% -------------------- DFE --------------------
|
||||
dfe_order2 = [50, 0, 0];
|
||||
eq_dfe = EQ("Ne",dfe_order2,"Nb",[2,0,0], ...
|
||||
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);
|
||||
@@ -356,6 +474,8 @@ eq_dfe = EQ("Ne",dfe_order2,"Nb",[2,0,0], ...
|
||||
dfe_results = ffe(eq_dfe,s.M,Rx_sig,Symbols_l,Tx_bits_l, ...
|
||||
"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
|
||||
"eth_style_symbol_mapping",0);
|
||||
clear eq_dfe
|
||||
log_mem(logfile, 'after_dfe', l, ri, realiz, eval_ptr, rop_db);
|
||||
|
||||
% -------------------- VNLE + MLSE --------------------
|
||||
pf_ncoeffs = 1;
|
||||
@@ -371,11 +491,22 @@ mlse_ = MLSE("duobinary_output",0,'M',s.M,'trellis_states',PAMmapper(s.M,0).leve
|
||||
[vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, s.M, Rx_sig, Symbols_l, Tx_bits_l, ...
|
||||
"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [], "eth_style_symbol_mapping", 0);
|
||||
|
||||
clear eq_v pf_ mlse_
|
||||
log_mem(logfile, 'after_vnle_mlse', l, ri, realiz, eval_ptr, rop_db);
|
||||
|
||||
% -------------------- DB target --------------------
|
||||
mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",s.M,'trellis_states',PAMmapper(s.M,0).levels);
|
||||
|
||||
dbt_results = duobinary_target(eq_v, mlse_db_, s.M, Rx_sig, Symbols_l, Tx_bits_l, ...
|
||||
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_, s.M, Rx_sig, Symbols_l, Tx_bits_l, ...
|
||||
"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", []);
|
||||
|
||||
clear mlse_db_
|
||||
log_mem(logfile, 'job_end', l, ri, realiz, eval_ptr, rop_db);
|
||||
|
||||
% Rx_sig no longer needed
|
||||
clear Rx_sig Symbols_l Tx_bits_l
|
||||
end
|
||||
|
||||
|
||||
@@ -385,15 +516,12 @@ function [F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt]
|
||||
if nargin < 9, block = false; end
|
||||
if isempty(F), return; end
|
||||
|
||||
% Non-blocking mode: try to fetch as many finished as possible with timeout=0
|
||||
% Blocking mode: wait for at least one result (timeout=Inf), then keep draining with timeout=0
|
||||
if block
|
||||
timeout_first = Inf;
|
||||
else
|
||||
timeout_first = 0;
|
||||
end
|
||||
|
||||
% Fetch first (maybe blocking), then drain the rest non-blocking
|
||||
first = true;
|
||||
while ~isempty(F)
|
||||
if first
|
||||
@@ -406,12 +534,11 @@ while ~isempty(F)
|
||||
try
|
||||
[k, ffe_r, dfe_r, vnle_r, mlse_r, dbt_r] = fetchNext(F, timeout);
|
||||
catch
|
||||
% fetchNext throws if timeout=0 and nothing finished in some releases; treat as "nothing ready"
|
||||
break;
|
||||
end
|
||||
|
||||
if isempty(k)
|
||||
break; % nothing ready
|
||||
break;
|
||||
end
|
||||
|
||||
m = meta(k);
|
||||
@@ -422,8 +549,177 @@ while ~isempty(F)
|
||||
output_mlse{m.l, m.ri, m.realiz, m.eval_ptr} = mlse_r;
|
||||
output_dbt{m.l, m.ri, m.realiz, m.eval_ptr} = dbt_r;
|
||||
|
||||
% Remove completed future & meta entry (important: indices change afterwards)
|
||||
F(k) = [];
|
||||
meta(k) = [];
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
%% ========================= Memory logging helpers =========================
|
||||
|
||||
function logfile = make_worker_logfile(memlog_dir)
|
||||
% One file per worker process to avoid write contention.
|
||||
pid = get_pid_safe();
|
||||
t = getCurrentTask();
|
||||
if isempty(t)
|
||||
tid = -1;
|
||||
else
|
||||
tid = t.ID;
|
||||
end
|
||||
logfile = fullfile(memlog_dir, sprintf('memlog_pid%d_task%d.txt', pid, tid));
|
||||
end
|
||||
|
||||
function log_mem(logfile, tag, l, ri, realiz, eval_ptr, rop_db, varargin)
|
||||
% Append one line with RSS/VmSize plus optional "largest variable" info.
|
||||
% Uses /proc on Linux where available.
|
||||
ts = datetime('now','TimeZone','local','Format','yyyy-MM-dd HH:mm:ss.SSS');
|
||||
|
||||
[rssMB, vmsMB] = proc_mem_mb();
|
||||
|
||||
% Optional: include size of a specific variable/object if provided
|
||||
extra = "";
|
||||
if ~isempty(varargin)
|
||||
try
|
||||
x = varargin{1}; %#ok<NASGU>
|
||||
w = whos('x');
|
||||
extra = sprintf(' | x_bytes=%d', w.bytes);
|
||||
catch
|
||||
extra = " | x_bytes=NA";
|
||||
end
|
||||
end
|
||||
|
||||
line = sprintf('%s | %s | l=%d ri=%d realiz=%d eval=%d rop=%.3f | RSS=%.1fMB Vm=%.1fMB%s\n', ...
|
||||
char(ts), tag, l, ri, realiz, eval_ptr, rop_db, rssMB, vmsMB, extra);
|
||||
|
||||
fid = fopen(logfile, 'a');
|
||||
if fid ~= -1
|
||||
fwrite(fid, line);
|
||||
fclose(fid);
|
||||
end
|
||||
end
|
||||
|
||||
function [rssMB, vmsMB] = proc_mem_mb()
|
||||
% RSS/VmSize from /proc (Linux). Falls back to NaN if unavailable.
|
||||
rssMB = NaN; vmsMB = NaN;
|
||||
|
||||
if isunix
|
||||
try
|
||||
txt = fileread('/proc/self/status');
|
||||
rssMB = parse_kb_field(txt, 'VmRSS:') / 1024;
|
||||
vmsMB = parse_kb_field(txt, 'VmSize:') / 1024;
|
||||
return;
|
||||
catch
|
||||
% fall through
|
||||
end
|
||||
end
|
||||
|
||||
% Fallback (Windows): memory() sometimes works
|
||||
if ispc
|
||||
try
|
||||
m = memory;
|
||||
% MemUsedMATLAB is bytes
|
||||
rssMB = double(m.MemUsedMATLAB) / 1024^2;
|
||||
vmsMB = NaN;
|
||||
catch
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
function kb = parse_kb_field(txt, key)
|
||||
kb = NaN;
|
||||
idx = strfind(txt, key);
|
||||
if isempty(idx), return; end
|
||||
i = idx(1) + length(key);
|
||||
% read until end of line
|
||||
j = find(txt(i:end)==newline, 1, 'first') + i - 2;
|
||||
val = strtrim(txt(i:j));
|
||||
% format: "123456 kB"
|
||||
parts = split(val);
|
||||
kb = str2double(parts{1});
|
||||
end
|
||||
|
||||
function pid = get_pid_safe()
|
||||
pid = -1;
|
||||
try
|
||||
pid = feature('getpid');
|
||||
catch
|
||||
% no-op
|
||||
end
|
||||
end
|
||||
|
||||
function [F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt] = ...
|
||||
throttle_inflight(F, meta, output_ffe, output_dfe, output_vnle, output_mlse, output_dbt, maxInFlight)
|
||||
%THROTTLE_INFLIGHT
|
||||
% Enforces a HARD cap on outstanding futures (running + queued + finished-not-yet-fetched).
|
||||
% Blocks until numel(F) < maxInFlight, then returns.
|
||||
|
||||
while numel(F) >= maxInFlight
|
||||
|
||||
% Wait until at least one finishes OR fails
|
||||
% (wait('finished',1) only wakes for finished, so we also handle failures via periodic checks)
|
||||
try
|
||||
wait(F, 'finished', 1);
|
||||
catch
|
||||
% If wait fails for some reason, fall back to a short pause
|
||||
pause(0.1);
|
||||
end
|
||||
|
||||
% Harvest finished and failed futures (robust snapshot)
|
||||
n = numel(F);
|
||||
|
||||
% Safety: meta must match F length
|
||||
if numel(meta) ~= n
|
||||
% Keep them aligned (rare; indicates earlier mismatch)
|
||||
m = min(numel(meta), n);
|
||||
F = F(1:m);
|
||||
meta = meta(1:m);
|
||||
n = m;
|
||||
end
|
||||
|
||||
states = cell(1,n);
|
||||
for k = 1:n
|
||||
states{k} = F(k).State;
|
||||
end
|
||||
|
||||
doneFinished = strcmp(states, 'finished');
|
||||
doneFailed = strcmp(states, 'failed');
|
||||
done = doneFinished | doneFailed;
|
||||
|
||||
idxDone = find(done);
|
||||
|
||||
if isempty(idxDone)
|
||||
pause(0.05);
|
||||
continue;
|
||||
end
|
||||
|
||||
% Fetch outputs for finished; mark failed as empty results
|
||||
for jj = 1:numel(idxDone)
|
||||
ii = idxDone(jj);
|
||||
m = meta(ii);
|
||||
|
||||
if doneFinished(ii)
|
||||
[ffe_r, dfe_r, vnle_r, mlse_r, dbt_r] = fetchOutputs(F(ii));
|
||||
else
|
||||
% Failed
|
||||
try
|
||||
err = F(ii).Error;
|
||||
warning('rx_job failed: realiz=%d eval=%d l=%d ri=%d | %s', ...
|
||||
m.realiz, m.eval_ptr, m.l, m.ri, err.message);
|
||||
catch
|
||||
end
|
||||
ffe_r = []; dfe_r = []; vnle_r = []; mlse_r = []; dbt_r = [];
|
||||
end
|
||||
|
||||
output_ffe{m.l, m.ri, m.realiz, m.eval_ptr} = ffe_r;
|
||||
output_dfe{m.l, m.ri, m.realiz, m.eval_ptr} = dfe_r;
|
||||
output_vnle{m.l, m.ri, m.realiz, m.eval_ptr} = vnle_r;
|
||||
output_mlse{m.l, m.ri, m.realiz, m.eval_ptr} = mlse_r;
|
||||
output_dbt{m.l, m.ri, m.realiz, m.eval_ptr} = dbt_r;
|
||||
end
|
||||
|
||||
% Remove harvested futures/meta entries using numeric indices (safe)
|
||||
F(idxDone) = [];
|
||||
meta(idxDone) = [];
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
Reference in New Issue
Block a user