170 lines
6.1 KiB
Matlab
170 lines
6.1 KiB
Matlab
function output = mpi_recipe_dev(Scpe_sig_raw, Symbols, Tx_bits, options)
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%mpi_recipe_dev Minimal example recipe for the DSP job framework.
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% This recipe intentionally performs only light preprocessing and records
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% summary values. It demonstrates the recipe interface without running a
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% full equalizer chain.
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arguments
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Scpe_sig_raw
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Symbols
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Tx_bits
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options.fsym
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options.M
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options.duob_mode
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options.dataTable table
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options.userParameters struct = struct()
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options.debug_plots (1,1) logical = false
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end
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Scpe_sig = preprocessSignal(Scpe_sig_raw, Symbols, options.fsym, ...
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"mode", "auto", ...
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"debug_plots", options.debug_plots);
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eq_settings = { ...
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"epochs_tr", 5, ...
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"epochs_dd", 5, ...
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"len_tr", 4096, ...
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"mu_tr",0.04, ...
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"mu_dd",0.012, ...
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"mu_dc", 0.012, ...
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"adaptive_dc_enabled", 0, ...
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"order", 25, ...
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"sps", 2, ...
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"decide", 0, ...
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"optmize_mus", 0, ...
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"dd_mode", 1, ...
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"adaption_technique", "nlms", ...
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"plot_mu_optimization", options.debug_plots,...
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"save_debug",true};
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eq_ffe = FFE(eq_settings{:});
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showLevelScatter(Scpe_sig_raw, Symbols, ...
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"fsym", options.fsym, ...
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"fignum", 400, ...
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"normalize", true);
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% Scpe_sig_raw.spectrum("normalizeTo0dB",1,"fft_length",4096*4,"fignum",401);
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%options.dataTable.sir;
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%% NORMAL FFE
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if 1
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[ffe_results,equalized_signal] = ffe(eq_ffe, options.M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", options.duob_mode, ...
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'showAnalysis', options.debug_plots, ...
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"postFFE", [], ...
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"eth_style_symbol_mapping", 0);
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ffe_results.metrics.print("description",sprintf('Normal FFE; SIR %d dB',options.dataTable.sir));
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output.ffe_package = ffe_results;
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[~, avg_for_lvl] = showLevelScatter(equalized_signal, Symbols, ...
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"fsym", options.fsym, ...
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"fignum", 401, ...
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"normalize", true);
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output.ffe_debug = struct();
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dbg = eq_ffe.debug_struct;
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smooth_len = 501;
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output.ffe_debug.smoothing_window = smooth_len;
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error_first_s = movmean(dbg.error_first_epoch(:),smooth_len,"omitnan");
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error_last_s = movmean(dbg.error(:),smooth_len,"omitnan");
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mu_dc_eff_s = movmean(dbg.mu_dc_eff(:),smooth_len,"omitnan");
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e_dc_eff_s = movmean(dbg.e_dc_eff(:),smooth_len,"omitnan");
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figure(460); clf;
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tiledlayout(2,1,"TileSpacing","compact","Padding","compact");
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nexttile;
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semilogy(error_first_s + eps,"DisplayName","first epoch");
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hold on;
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semilogy(error_last_s + eps,"DisplayName","last epoch");
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grid on;
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ylabel("error");
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title("FFE debug error");
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legend("Location","best");
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nexttile;hold on
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% plot(eq_sig_mov,"DisplayName","err dc eff");
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plot(mu_dc_eff_s,"DisplayName","mu DC - either fixed or adaptive");
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e_dc_scale = max(abs(e_dc_eff_s),[],"omitnan") + eps;
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plot(-1.*e_dc_eff_s./e_dc_scale,"DisplayName","Inverted DC-tracking; Value that is subtracted during EQ");
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avg_lvl_dc=mean(avg_for_lvl,1,"omitnan");
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plot(avg_lvl_dc./0.01,"DisplayName","Smoothed EQ output signal; calc'd by showLevelScatter");
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grid on;
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xlabel("Symbol");
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ylabel("mu dc eff");
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title("Effective adaptive DC step");
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legend
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inv_dc_track = -e_dc_eff_s(:);
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avg_lvl_dc = avg_lvl_dc(:);
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xcorr_len = min(numel(inv_dc_track),numel(avg_lvl_dc));
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inv_dc_xcorr = inv_dc_track(1:xcorr_len);
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avg_lvl_xcorr = avg_lvl_dc(1:xcorr_len);
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inv_dc_xcorr = fillmissing(inv_dc_xcorr,"linear","EndValues","nearest");
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avg_lvl_xcorr = fillmissing(avg_lvl_xcorr,"linear","EndValues","nearest");
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inv_dc_xcorr = inv_dc_xcorr - mean(inv_dc_xcorr,"omitnan");
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avg_lvl_xcorr = avg_lvl_xcorr - mean(avg_lvl_xcorr,"omitnan");
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[dc_level_xcorr,dc_level_lags] = xcorr(inv_dc_xcorr,avg_lvl_xcorr,"coeff");
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[dc_level_corr,dc_level_idx] = max(dc_level_xcorr);
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dc_level_delay_symbols = dc_level_lags(dc_level_idx);
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output.ffe_debug.dc_level_delay_symbols = dc_level_delay_symbols;
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output.ffe_debug.dc_level_delay_corr = dc_level_corr;
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output.ffe_debug.dc_level_lags = dc_level_lags;
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output.ffe_debug.dc_level_xcorr = dc_level_xcorr;
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fprintf("FFE debug: xcorr(inv DC tracking, avg level) delay=%d symbols, corr=%6.3f\n", ...
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dc_level_delay_symbols,dc_level_corr);
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figure(461); clf;
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plot(dc_level_lags,dc_level_xcorr,"DisplayName","xcorr");
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hold on;
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plot(dc_level_delay_symbols,dc_level_corr,"ro","DisplayName","max");
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grid on;
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xlabel("Lag in symbols");
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ylabel("Correlation coefficient");
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title(sprintf("Delay estimate: %d symbols (corr %.3f)",dc_level_delay_symbols,dc_level_corr));
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legend("Location","best");
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end
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%% MPI Reduction
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if 1
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% dc_buffer_len = 0;
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% ffe_buffer_len = 0;
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% smoothing_buffer_length = options.userParameters.smoothing_length;
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% smoothing_buffer_update = 1;
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% eq_ffe_dcr = FFE_DCremoval_adaptive_mu(eq_settings{:}, ...
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% "dc_buffer_len",dc_buffer_len, ...
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% "ffe_buffer_len",ffe_buffer_len,...
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% "smoothing_buffer_length",smoothing_buffer_length,...
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% "smoothing_buffer_update",smoothing_buffer_update);
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eq_ = FFE_DCremoval("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
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0.0002,"mu_tr",0,"order",25,"sps",2,"decide",0,...
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"mu_dc",0.005,"dc_buffer_len",1);
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ffe_results_dcr = ffe(eq_, options.M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", options.duob_mode, ...
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'showAnalysis', options.debug_plots, ...
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"postFFE", [], ...
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"eth_style_symbol_mapping", 0);
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ffe_results_dcr.metrics.print("description",'FFE DCR');
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output.ffe_dcr_package = ffe_results_dcr;
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end
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end
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