BCJR implementation
WDM code added (Pol Cont., Opt MUX/DEMUX, Opt Atten, DP_Fiber) -> the codebase is not optimized to always work with dp signals!
This commit is contained in:
Silas Oettinghaus
@@ -4,30 +4,39 @@ dataBase = 'labor_highspeed';%'C:\Users\Silas\Documents\MATLAB\Datensätze\sio
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db = DBHandler("dataBase", [dataBase], "type", database_type);
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fp = QueryFilter();
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% fp.where('Runs', 'run_id','EQUALS', 987);
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% fp.where('Runs', 'run_id','EQUALS', 987);
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M = 8;
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fp.where('Runs', 'pam_level','EQUALS', M);
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% fp.where('Runs', 'bitrate','LESS_THAN', 310e9);
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fp.where('Runs', 'fiber_length','EQUALS', 2);
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fp.where('Runs', 'is_mpi','EQUALS', 0);
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% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
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% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
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% fp.where('Runs', 'sir','EQUALS',18);
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fp.where('Runs', 'wavelength','EQUALS', 1310);
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% fp.where('Runs', 'db_mode','EQUALS', 1);
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fp.where('Runs', 'rop_attenuation','EQUALS', 0);
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fp.where('Runs', 'pam_level','EQUALS', M);
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% fp.where('Runs', 'bitrate','LESS_THAN', 310e9);
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fp.where('Runs', 'fiber_length','EQUALS', 2);
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fp.where('Runs', 'is_mpi','EQUALS', 0);
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% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
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% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
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% fp.where('Runs', 'sir','EQUALS',18);
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fp.where('Runs', 'wavelength','EQUALS', 1293);
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% fp.where('Runs', 'db_mode','EQUALS', 0);
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fp.where('Runs', 'rop_attenuation','EQUALS', 0);
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% [dataTable,~] = db.queryDB(fp, db.getTableFieldNames('dashboard'));
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fields = db.getTableFieldNames('power_state_info');
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fields = [fields; db.getTableFieldNames('dashboard_ungrouped_new')];
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[dataTable,~] = db.queryDB(fp, fields);
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eqstructures = unique(dataTable.equalizer_structure);
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% Create the figure
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figure(10);
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showFiltered = true;
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showPrecoded = false;
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show_bitrate = true;
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figure(5);
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hold on
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for pre_emph = [1]
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dbmode_filtered = dataTable(dataTable.db_mode == ~pre_emph,:);
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for eqs = [equalizer_structure.vnle, equalizer_structure.vnle_pf_mlse , equalizer_structure.vnle_db_mlse]
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for eqs = [equalizer_structure.vnle, equalizer_structure.vnle_pf_mlse]
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% figure('Name',string([char(eqs),'']));
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% hold on
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for pre_emph = [0,1]
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dbmode_filtered = dataTable(dataTable.db_mode == ~pre_emph,:);
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eq_choice = equalizer_structure(eqs);
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@@ -37,50 +46,238 @@ for pre_emph = [1]
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end
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eq_filtered = dbmode_filtered(dbmode_filtered.equalizer_structure == eq_choice,:);
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symbolrate_sorted = sortrows(eq_filtered,{'symbolrate','min_BER_precoded'}, 'ascend');
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[~, ia] = unique(symbolrate_sorted.symbolrate, 'first');
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% ===== NEW: compute averages + per-row keep masks (robust filtering) =====
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[Tav, keepMask, keepMaskP] = avgBerBySymbolrate(eq_filtered); % <= NEW
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% x-values (bitrate) for raw points (same mapping as your lines)
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M = unique(eq_filtered.pam_level); % (assumes single PAM per curve)
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if show_bitrate
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x_raw = eq_filtered.symbolrate.*1e-9 .* floor(log2(M)*10)/10;
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else
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x_raw = eq_filtered.symbolrate.*1e-9;
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end
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% ===== NEW: scatter kept raw BER points (hidden from legend) =====
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cols = cbrewer2('Paired',12);
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thisColor = cols((2*eqs)+1+pre_emph,:);
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scatter(x_raw(keepMask), ... % kept points
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eq_filtered.BER(keepMask), ...
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14, thisColor, 'filled', ...
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'MarkerFaceAlpha', 0.35, ...
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'MarkerEdgeAlpha', 0.35, ...
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'HandleVisibility','off');
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if showPrecoded
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scatter(x_raw(keepMaskP), ... % kept precoded points
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eq_filtered.BER_precoded(keepMaskP), ...
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14, thisColor, 'filled', ...
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'Marker', 'square', ...
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'MarkerFaceAlpha', 0.35, ...
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'MarkerEdgeAlpha', 0.35, ...
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'HandleVisibility','off');
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end
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% ===== NEW: optionally show filtered-out points in red =====
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if showFiltered
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bad = ~keepMask;
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if any(bad)
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scatter(x_raw(bad), eq_filtered.BER(bad), ...
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18, 'r', 'x', 'LineWidth', 1.2, ...
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'HandleVisibility','off');
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end
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badp = ~keepMaskP;
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if any(badp)
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scatter(x_raw(badp), eq_filtered.BER_precoded(badp), ...
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18, 'r', '+', 'LineWidth', 1.2, ...
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'HandleVisibility','off');
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end
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end
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% Keep your sorting and one-per-symbolrate behavior (using Tav)
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symbolrate_sorted = sortrows(Tav,{'symbolrate','avg_BER_calc'}, 'ascend');
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[~, ia] = unique(symbolrate_sorted.symbolrate, 'first');
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symbolrate_sorted = symbolrate_sorted(ia, :);
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% Example data (replace these with your real vectors)
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symbolrate = symbolrate_sorted.symbolrate.*1e-9; % in baud
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bitrate = symbolrate * floor(log2(M)*10)/10;
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ber = symbolrate_sorted.min_BER; % BER
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ber_precoded = symbolrate_sorted.min_BER_precoded; % BER
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cols = cbrewer2('Paired',12);
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cols = [0.4660 0.6740 0.1880 ; 0.9290 0.6940 0.1250 ; 0 0.4470 0.7410; 0.4940 0.1840 0.5560]; %VNLE; PF ; DFE ; DB tgt
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dname = [char(eq_choice)];
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if pre_emph
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if show_bitrate
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% Bitrate for the averaged curves (unchanged)
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xraw = symbolrate_sorted.symbolrate.*1e-9 .* floor(log2(M)*10)/10;
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else
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xraw = symbolrate_sorted.symbolrate.*1e-9;
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end
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% Use the MATLAB-averaged BERs
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ber = symbolrate_sorted.avg_BER_calc;
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ber_precoded = symbolrate_sorted.avg_BER_precoded_calc;
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dname = strrep([char(eq_choice)],'_',' ');
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if pre_emph
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dname = [dname,' with pre-emph.'];
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else
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dname = [dname,' w/o pre-emph.'];
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end
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plot(bitrate, ber, 'LineWidth', 1.5, 'MarkerSize', 5,'Marker','o','LineStyle','-','Color',cols((2*eqs)+1+pre_emph,:),'MarkerEdgeColor',cols((2*eqs)+1+pre_emph,:),'MarkerFaceColor',[1,1,1],'DisplayName',[dname]);
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plot(bitrate, ber_precoded, 'LineWidth', 1.5, 'MarkerSize', 5,'Marker','square','LineStyle',':','Color',cols((2*eqs)+1+pre_emph,:),'MarkerEdgeColor',cols((2*eqs)+1+pre_emph,:),'MarkerFaceColor',[1,1,1],'DisplayName',[dname,'; pre-coded']);
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grid on;
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% Axis labels and title
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xlabel('Baud Rate GBaud', 'FontSize', 12);
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ylabel('BER', 'FontSize', 12);
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title('BER vs. Baud Rate', 'FontSize', 14, 'FontWeight', 'bold');
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% Improve tick formatting
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set(gca, 'XScale', 'linear', ...
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'YScale', 'log', ...
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'TickLabelInterpreter', 'latex', ...
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'FontSize', 11);
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legend
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plot(xraw, ber, ...
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'LineWidth', 1.5, 'MarkerSize', 5, ...
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'Marker','o','LineStyle','-', ...
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'Color',thisColor,'MarkerEdgeColor',thisColor,'MarkerFaceColor',[1,1,1], ...
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'DisplayName', dname);
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xticks(bitrate);
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if showPrecoded
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plot(xraw, ber_precoded, ...
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'LineWidth', 1.5, 'MarkerSize', 5, ...
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'Marker','square','LineStyle',':', ...
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'Color',thisColor,'MarkerEdgeColor',thisColor,'MarkerFaceColor',[1,1,1], ...
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'DisplayName', [dname,'; pre-coded']);
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end
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grid on;
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if show_bitrate
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xlabel('Net bitrate [GBps]', 'FontSize', 12);
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else
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xlabel('Symbol rate [GBd]', 'FontSize', 12);
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end
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ylabel('BER', 'FontSize', 12);
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title('BER vs. Baud Rate','FontSize', 14, 'FontWeight', 'bold');
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set(gca, 'XScale', 'linear', ...
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'YScale', 'log', ...
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'TickLabelInterpreter', 'latex', ...
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'FontSize', 11);
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% Optional: tighten axis limits
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xlim([min(bitrate), max(bitrate)]);
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ylim([5e-5, 0.5]);
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xticks(xraw);
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if show_bitrate
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xticks(200:25:500);
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xlim([350 500]);
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else
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xlim([min(xraw), max(xraw)]);
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end
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ylim([5e-4, 0.3]);
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end
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yline([2.2e-4, 4.85e-3, 2e-2],'LineWidth',1,'LineStyle','--','HandleVisibility','off');
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end
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function [Tav, keepAll, keepAllP] = avgBerBySymbolrate(T, ZT, MIN_G)
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% Minimal robust averaging of BER per symbolrate (+ masks for kept points).
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% Usage: [Tav, keepAll, keepAllP] = avgBerBySymbolrate(T, ZT, MIN_G)
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% Defaults: ZT=3 (MAD z-thresh in log10), MIN_G=2 (min points to filter)
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if nargin < 2, ZT = 5; end
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if nargin < 5, MIN_G = 0; end
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hasP = ismember('BER_precoded', T.Properties.VariableNames);
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hasNB = ismember('numBits', T.Properties.VariableNames);
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[G,~,idx] = unique(T.symbolrate);
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nG = numel(G);
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avgBER = nan(nG,1);
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avgBERp = nan(nG,1);
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keepAll = false(height(T),1);
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keepAllP = false(height(T),1);
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for gi = 1:nG
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r = idx==gi;
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x = T.BER(r);
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nb = hasNB * T.numBits(r) + ~hasNB; % if missing, nb==1 (scalar expansion ok)
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[avgBER(gi), keepAll(r)] = rmeanBer(x, nb, ZT, MIN_G);
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if hasP
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xp = T.BER_precoded(r);
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[avgBERp(gi), keepAllP(r)] = rmeanBer(xp, nb, ZT, MIN_G);
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end
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end
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Tav = table(G, avgBER, avgBERp, ...
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'VariableNames', {'symbolrate','avg_BER_calc','avg_BER_precoded_calc'});
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end
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function [mu, keep] = rmeanBer(x, nb, ZT, MIN_G, onlyHighOutliers, minKeepThreshold)
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% Robust arithmetic mean of BER with log-domain MAD filtering (returns keep mask)
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%
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% Params:
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% x : BER values
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% nb : numBits (for floor)
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% ZT : MAD z-threshold
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% MIN_G : min group size before filtering
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% onlyHighOutliers : (bool) if true, only discard values above mean
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% minKeepThreshold : values below this BER are always kept
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%
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% Returns:
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% mu : robust mean
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% keep : logical mask of kept samples
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if nargin < 5, onlyHighOutliers = false; end
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if nargin < 6, minKeepThreshold = 0; end
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x(~isfinite(x)) = NaN;
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if ~isscalar(nb), nb(~isfinite(nb)) = NaN; end
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if isscalar(nb) && ~isfinite(nb), nb = 1; end
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floorVal = realmin;
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if ~isscalar(nb) || (isscalar(nb) && isfinite(nb) && nb~=1)
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fv = 0.5 ./ max(nb, eps); % rule-of-three style floor
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if isscalar(fv), floorVal = fv; else, floorVal = fv; end
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end
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xAdj = x;
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bad = ~isfinite(xAdj) | xAdj <= 0;
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if isscalar(floorVal)
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xAdj(bad) = floorVal;
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else
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xAdj(bad) = floorVal(bad);
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end
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valid = isfinite(xAdj) & xAdj > 0;
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keep = false(size(xAdj));
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if nnz(valid)==0
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mu = NaN; return
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end
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if nnz(valid) < MIN_G
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mu = mean(xAdj(valid),'omitnan'); keep(valid)=true; return
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end
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lx = log10(xAdj(valid));
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med = median(lx,'omitnan');
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mad = median(abs(lx-med),'omitnan');
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if mad<=0 || ~isfinite(mad)
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keep(valid) = true;
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mu = mean(xAdj(valid),'omitnan');
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return
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end
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sigma = 1.4826*mad;
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ksel = abs(lx-med) <= ZT*sigma;
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% convert to linear indices
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vIdx = find(valid);
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% === Extension A: only drop high outliers ===
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if onlyHighOutliers
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logMean = mean(lx,'omitnan');
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highIdx = lx > logMean;
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ksel = ksel | ~highIdx; % always keep values below/equal to mean
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end
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% === Extension B: always keep values below minKeepThreshold ===
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belowThr = xAdj(valid) < minKeepThreshold;
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ksel = ksel | belowThr;
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keep(vIdx(ksel)) = true;
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if any(keep)
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mu = mean(xAdj(keep),'omitnan');
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else
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mu = mean(xAdj(valid),'omitnan');
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keep(valid) = true;
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end
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end
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yline([4.85e-3, 2e-2],'LineWidth',1,'LineStyle','--','HandleVisibility','off'); beautifyBERplot();
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@@ -1,6 +1,6 @@
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% === SETTINGS ===
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dsp_options.append_to_db = 0;
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dsp_options.max_occurences = 1;
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dsp_options.append_to_db = 1;
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dsp_options.max_occurences = 15;
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experiment = "highspeed_2024";
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dsp_options.mode = "load_run_id"; % 'simulate' & 'load_files'
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@@ -39,29 +39,23 @@ end
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% === Get Run ID's ===
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fp = QueryFilter();
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% fp.where('Runs', 'run_id','EQUALS', 987);
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fp.where('Runs', 'pam_level','EQUALS', 4);
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fp.where('Runs', 'bitrate','EQUALS', 360e9);
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fp.where('Runs', 'fiber_length','EQUALS', 2);
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% fp.where('Runs', 'run_id','EQUALS', 987);
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M = 6;
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% fp.where('Runs', 'pam_level','EQUALS', M);
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% fp.where('Runs', 'bitrate','EQUALS', 480e9);
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% fp.where('Runs', 'symbolrate','EQUALS', 162e9);
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fp.where('Runs', 'fiber_length','EQUALS', 1);
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fp.where('Runs', 'is_mpi','EQUALS', 0);
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% fp.where('Runs', 'interference_path_length','EQUALS', 1000);
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% fp.where('Runs', 'loop_id','GREATER_THAN', 11);
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% fp.where('Runs', 'sir','EQUALS',18);
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fp.where('Runs', 'wavelength','EQUALS', 1310);
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fp.where('Runs', 'db_mode','EQUALS', 0);
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fp.where('Runs', 'rop_attenuation','EQUALS', 0);
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fp.where('Runs', 'wavelength','LESS_THAN', 1311);
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% fp.where('Runs', 'db_mode','EQUALS', 0);
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% fp.where('Runs', 'rop_attenuation','NOT_EQUAL', 0);
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% fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
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[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
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% Keep only the rows corresponding to the first occurrence of each 'sir' value
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% [~, unique_indices] = unique(dataTable.sir, 'first');
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% dataTable = dataTable(unique_indices, :);
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% dataTable = dataTable(1,:);
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% === Set LOOPS & Initialize DataStorage ===
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dsp_options.parameters = struct();
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% dsp_options.parameters.pf_ncoeffs = [1,2];%[0,logspace(-4,0,10)];
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@@ -75,150 +69,281 @@ wh.addStorage("dbenc_package");
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% === RUN IT ===
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[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "serial", 'wh', wh, 'waitbar', true);
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[results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "parallel", 'wh', wh, 'waitbar', true);
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results_db = results(dataTable.db_mode==1);
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results_nodb = results(dataTable.db_mode==0);
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for i = 1:numel(results_db)
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% VNLE (from results_nodb)
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gmi_v = cellfun(@(c) c.metrics.GMI, results_nodb{1,i}.vnle_package);
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ber_v = cellfun(@(c) c.metrics.BER, results_nodb{1,i}.vnle_package);
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air_v = cellfun(@(c) c.metrics.AIR, results_nodb{1,i}.vnle_package);
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snr_v = cellfun(@(c) c.metrics.SNR, results_nodb{1,i}.vnle_package);
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[BER_VNLE(i), idx_ber] = min(ber_v);
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GMI_VNLE(i) = gmi_v(idx_ber);
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AIR_VNLE(i) = air_v(idx_ber);
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SNR_VNLE(i) = max(snr_v);
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idx_gmi_min_vnle(i) = find(gmi_v == min(gmi_v), 1);
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idx_air_max_vnle(i) = find(air_v == max(air_v), 1);
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% MLSE (from results_db)
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gmi_m = cellfun(@(c) c.metrics.GMI, results_nodb{1,i}.mlse_package);
|
||||
ber_m = cellfun(@(c) c.metrics.BER, results_nodb{1,i}.mlse_package);
|
||||
air_m = cellfun(@(c) c.metrics.AIR, results_nodb{1,i}.mlse_package);
|
||||
[BER_MLSE(i), idx_ber] = min(ber_m);
|
||||
GMI_MLSE(i) = gmi_m(idx_ber);
|
||||
AIR_MLSE(i) = air_m(idx_ber);
|
||||
idx_gmi_min_mlse(i) = find(gmi_m == min(gmi_m), 1);
|
||||
idx_air_max_mlse(i) = find(air_m == max(air_m), 1);
|
||||
|
||||
% DB (from results_db, BER_precoded)
|
||||
gmi_db = cellfun(@(c) c.metrics.GMI, results_db{1,i}.dbtgt_package);
|
||||
ber_db = cellfun(@(c) c.metrics.BER, results_db{1,i}.dbtgt_package);
|
||||
ber_db_prec = cellfun(@(c) c.metrics.BER_precoded, results_db{1,i}.dbtgt_package);
|
||||
air_db = cellfun(@(c) c.metrics.AIR, results_db{1,i}.dbtgt_package);
|
||||
[BER_DB(i), idx_ber] = min(ber_db);
|
||||
[BER_DB_PREC(i), idx_ber] = min(ber_db_prec);
|
||||
|
||||
GMI_DB(i) = gmi_db(idx_ber);
|
||||
AIR_DB(i) = air_db(idx_ber);
|
||||
idx_gmi_min_db(i) = find(gmi_db == min(gmi_db), 1);
|
||||
idx_air_max_db(i) = find(air_db == max(air_db), 1);
|
||||
|
||||
% metadata
|
||||
bitrate(i) = dataTable.bitrate(i);
|
||||
baudrate(i) = dataTable.symbolrate(i);
|
||||
end
|
||||
|
||||
STYLE_BASE = 2; % adjust this single number to scale markers & lines
|
||||
MARKER_SIZE = STYLE_BASE; % marker size (MATLAB MarkerSize)
|
||||
LINE_WIDTH = max(2, STYLE_BASE/3); % line width (keeps lines reasonable when STYLE_BASE large)
|
||||
|
||||
% --- color map / method -> color assignment (keeps colors consistent) ---
|
||||
cols = cbrewer2('Paired',8);
|
||||
cols = linspecer(6);
|
||||
d = 0;
|
||||
cm.VNLE = cols(1 + d, :);
|
||||
cm.MLSE = cols(2 + d, :);
|
||||
cm.DB_precode = cols(3 + d, :);
|
||||
cm.DB = cols(4 + d, :); % duobinary
|
||||
|
||||
% prepare x values in GBd
|
||||
xGHz = baudrate .* 1e-9;
|
||||
xticks_vals = xGHz;
|
||||
xtick_labels = arrayfun(@(v) sprintf('%d', round(v)), xticks_vals, 'UniformOutput', false);
|
||||
|
||||
% common marker settings (filled, same face+edge color)
|
||||
mk.VNLE = {'Marker','o','MarkerFaceColor',cm.VNLE,'MarkerEdgeColor',cm.VNLE,'MarkerSize',MARKER_SIZE};
|
||||
mk.MLSE = {'Marker','*','MarkerFaceColor',cm.MLSE,'MarkerEdgeColor',cm.MLSE,'MarkerSize',MARKER_SIZE};
|
||||
mk.DB_precode = {'Marker','^','MarkerFaceColor',cm.DB_precode,'MarkerEdgeColor',cm.DB_precode,'MarkerSize',MARKER_SIZE};
|
||||
mk.DB = {'Marker','d','MarkerFaceColor',cm.DB,'MarkerEdgeColor',cm.DB,'MarkerSize',MARKER_SIZE};
|
||||
|
||||
|
||||
% wh.getStoValue('ffe_package',0.005);
|
||||
% wh.getStoValue('mlse_package',0.005);
|
||||
% ---------------- FIGURE : BER ----------------
|
||||
figure(112+M); clf; hold on;
|
||||
plot(xGHz, BER_VNLE, ...
|
||||
'DisplayName','VNLE', ...
|
||||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, BER_MLSE, ...
|
||||
'DisplayName','MLSE', ...
|
||||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
plot(xGHz, BER_DB, ...
|
||||
'DisplayName','DB tgt.', ...
|
||||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
plot(xGHz, BER_DB_PREC, ...
|
||||
'DisplayName','Diff. Precode + DB tgt.', ...
|
||||
mk.DB{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
yline(4.85e-3,'LineWidth',1,'HandleVisibility','off');
|
||||
yline(2.2e-4,'LineWidth',1,'HandleVisibility','off');
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('BER');
|
||||
set(gca, 'yscale', 'log');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
|
||||
% [dataTable,~] = db.queryDB(fp, [db.getTableFieldNames('Runs');db.getTableFieldNames('Results');db.getTableFieldNames('Equalizer')]);
|
||||
|
||||
% ---------------- FIGURE 15 : GMI ----------------
|
||||
figure(113+M); clf; hold on;
|
||||
plot(xGHz, GMI_VNLE, ...
|
||||
'DisplayName','VNLE', ...
|
||||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, GMI_MLSE, ...
|
||||
'DisplayName','MLSE', ...
|
||||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
plot(xGHz, GMI_DB, ...
|
||||
'DisplayName','DB tgt.', ...
|
||||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
|
||||
ylim([log2(M)-1, log2(M)]);
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('GMI');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
|
||||
|
||||
|
||||
% ---------------- FIGURE 15 : AIR ----------------
|
||||
m = floor(log2(M)*10)/10;
|
||||
figure(114+M); clf; hold on;
|
||||
plot(xGHz, GMI_VNLE.*xGHz, ...
|
||||
'DisplayName','AIR VNLE', ...
|
||||
mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
% duobinary has only one GMI curve (DB output)
|
||||
plot(xGHz, GMI_MLSE.*xGHz, ...
|
||||
'DisplayName','AIR MLSE', ...
|
||||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
% MLSE symbol-wise (if present)
|
||||
plot(xGHz, GMI_DB.*xGHz, ...
|
||||
'DisplayName','AIR DB tgt.', ...
|
||||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
|
||||
% ylim([log2(M)-1, log2(M)]);
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('AIR in Gbps');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
% ---------------- FIGURE 15 : Information Rates ----------------
|
||||
tp = TransmissionPerformance;
|
||||
|
||||
|
||||
m = floor(log2(M)*10)/10;
|
||||
figure(213+M); clf; hold on;
|
||||
|
||||
netrates_vnle = tp.calculateNetRate(baudrate.* m, ...
|
||||
'NGMI', GMI_VNLE./m, ...
|
||||
'BER', BER_VNLE);
|
||||
%
|
||||
% dataTable = cleanUpTable(dataTable);
|
||||
% wh_analyze = wh_adap;
|
||||
% % wh_analyze = wh_dcremoval_old2;
|
||||
% % wh_analyze = wh_dcremoval_old2;
|
||||
% plot(xGHz, GMI_VNLE.*xGHz, ...
|
||||
% 'DisplayName','GMI*R VNLE', ...
|
||||
% mk.VNLE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
%
|
||||
% 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;
|
||||
% plot(xGHz, netrates_vnle.SDHD.NetRate.*1e-9, ...
|
||||
% 'DisplayName','SD+HD VNLE', ...
|
||||
% mk.VNLE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
% plot(xGHz, netrates_vnle.HD.NetRate.*1e-9, ...
|
||||
% 'DisplayName','Staircase VNLE', ...
|
||||
% mk.VNLE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
%
|
||||
%
|
||||
% %
|
||||
% % MLSE symbol-wise (if present)
|
||||
% plot(xGHz, GMI_MLSE.*xGHz, ...
|
||||
% 'DisplayName','GMI*R MLSE', ...
|
||||
% mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
%
|
||||
%
|
||||
% 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;
|
||||
% netrates_mlse = tp.calculateNetRate(baudrate.* m, ...
|
||||
% 'NGMI', GMI_MLSE./m, ...
|
||||
% 'BER', BER_MLSE);
|
||||
% plot(xGHz, netrates_mlse.SDHD.NetRate.*1e-9, ...
|
||||
% 'DisplayName','SD+HD MLSE', ...
|
||||
% mk.MLSE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
% plot(xGHz, netrates_mlse.HD.NetRate.*1e-9, ...
|
||||
% 'DisplayName','Staircase MLSE', ...
|
||||
% mk.MLSE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
|
||||
|
||||
% duobinary has only one GMI curve (DB output)
|
||||
figure(1111); clf; hold on;
|
||||
plot(xGHz, GMI_DB.*xGHz, ...
|
||||
'DisplayName','GMI*R DB tgt.', ...
|
||||
mk.DB{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
|
||||
netrates_db = tp.calculateNetRate(baudrate.* m, ...
|
||||
'NGMI', GMI_DB./m, ...
|
||||
'BER', BER_DB_PREC);
|
||||
|
||||
plot(xGHz, netrates_db.SDHD.NetRate.*1e-9, ...
|
||||
'DisplayName','SD+HD DB', ...
|
||||
mk.DB{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.DB);
|
||||
plot(xGHz, netrates_db.STAIR.NetRate.*1e-9, ...
|
||||
'DisplayName','Staircase DB', ...
|
||||
mk.DB_precode{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.DB_precode);
|
||||
plot(xGHz, netrates_db.O_FEC.NetRate.*1e-9, ...
|
||||
'DisplayName','O-FEC DB', ...
|
||||
mk.DB_precode{:}, 'LineStyle','--','LineWidth',LINE_WIDTH,'Color',cm.DB_precode);
|
||||
plot(xGHz, netrates_db.KP4_hamming.NetRate.*1e-9, ...
|
||||
'DisplayName','KP4 Hamming DB', ...
|
||||
mk.DB_precode{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.DB_precode);
|
||||
|
||||
% ylim([log2(M)-1, log2(M)]);
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('AIR in Gbps');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
% xlim([1, 256])
|
||||
|
||||
|
||||
|
||||
figure(2222); clf; hold on;
|
||||
plot(xGHz, GMI_MLSE.*xGHz, ...
|
||||
'DisplayName','GMI*R DB tgt.', ...
|
||||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
|
||||
netrates_mlse = tp.calculateNetRate(baudrate.* m, ...
|
||||
'NGMI', GMI_MLSE./m, ...
|
||||
'BER', BER_MLSE);
|
||||
|
||||
plot(xGHz, netrates_mlse.SDHD.NetRate.*1e-9, ...
|
||||
'DisplayName','SD+HD DB', ...
|
||||
mk.MLSE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
plot(xGHz, netrates_mlse.STAIR.NetRate.*1e-9, ...
|
||||
'DisplayName','Staircase DB', ...
|
||||
mk.VNLE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, netrates_mlse.O_FEC.NetRate.*1e-9, ...
|
||||
'DisplayName','O-FEC DB', ...
|
||||
mk.VNLE{:}, 'LineStyle','--','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, netrates_mlse.KP4_hamming.NetRate.*1e-9, ...
|
||||
'DisplayName','KP4 Hamming DB', ...
|
||||
mk.VNLE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
|
||||
% ylim([log2(M)-1, log2(M)]);
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('AIR in Gbps');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
% xlim([1, 256])
|
||||
|
||||
|
||||
|
||||
figure(3333); clf; hold on;
|
||||
plot(xGHz, GMI_VNLE.*xGHz, ...
|
||||
'DisplayName','GMI*R DB tgt.', ...
|
||||
mk.MLSE{:}, 'LineStyle','-','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
|
||||
netrates_vnle = tp.calculateNetRate(baudrate.* m, ...
|
||||
'NGMI', GMI_VNLE./m, ...
|
||||
'BER', BER_VNLE);
|
||||
|
||||
plot(xGHz, netrates_vnle.SDHD.NetRate.*1e-9, ...
|
||||
'DisplayName','SD+HD DB', ...
|
||||
mk.MLSE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.MLSE);
|
||||
plot(xGHz, netrates_vnle.STAIR.NetRate.*1e-9, ...
|
||||
'DisplayName','Staircase DB', ...
|
||||
mk.VNLE{:}, 'LineStyle','-.','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, netrates_vnle.O_FEC.NetRate.*1e-9, ...
|
||||
'DisplayName','O-FEC DB', ...
|
||||
mk.VNLE{:}, 'LineStyle','--','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
plot(xGHz, netrates_vnle.KP4_hamming.NetRate.*1e-9, ...
|
||||
'DisplayName','KP4 Hamming DB', ...
|
||||
mk.VNLE{:}, 'LineStyle',':','LineWidth',LINE_WIDTH,'Color',cm.VNLE);
|
||||
|
||||
% ylim([log2(M)-1, log2(M)]);
|
||||
xlabel('Baudrate in GBd');
|
||||
ylabel('AIR in Gbps');
|
||||
set(gca, 'XTick', xticks_vals(1:2:end), 'XTickLabel', xtick_labels(1:2:end));
|
||||
grid on;
|
||||
legend('Location','best');
|
||||
% xlim([1, 256])
|
||||
Reference in New Issue
Block a user