319 lines
12 KiB
Matlab
319 lines
12 KiB
Matlab
function [output] = dsp_runid(run_id, options)
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arguments
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run_id
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options.append_to_db = 0;
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options.max_occurences = 4;
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options.parameters = struct();
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options.database_type
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options.dataBase
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options.load_file_path = struct();
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options.storage_path
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options.mode
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end
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try
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% Initialize output structures
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output.ffe_package = {};
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output.mlse_package = {};
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output.vnle_package = {};
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output.dbtgt_package = {};
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output.dbenc_package = {};
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output.mlmlse_package = {};
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if options.mode == "load_run_id" || options.append_to_db
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% Initialize database connection
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database = DBHandler("dataBase", [options.dataBase], "type", options.database_type );
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if 0
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% 2. Check if an equalizer configuration with the same hash exists
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queryStr = sprintf('SELECT COUNT(DISTINCT eq_id) AS unique_eq_count, COUNT(*) AS entries_for_run FROM `Results` WHERE run_id = %d', run_id);
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existing_results = database.fetch(queryStr);
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if existing_results.unique_eq_count >= 6
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if (existing_results.entries_for_run / existing_results.unique_eq_count) > 5
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return
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end
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end
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end
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end
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if options.mode == "load_run_id"
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dataTable = queryRunid(run_id, database);
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fsym = dataTable.symbolrate;
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M = double(dataTable.pam_level);
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duob_mode = db_mode(strrep(dataTable.db_mode,'"',''));
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% if database.checkIfRunExists('Results','run_id',run_id)
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% disp(['Already got at least one reulst for run id: ',num2str(run_id),' '])
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% return
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% end
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% Load and Sync signal data from DB
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[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncSignalDataFromDb(dataTable, options);
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elseif options.mode == "load_files"
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Tx_bits = load(options.load_file_path.tx_bits_path);
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Symbols = load(options.load_file_path.tx_symbols_path);
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Scpe_sig_raw = load(options.load_file_path.rx_raw_path);
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Tx_bits = Tx_bits.Bits;
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Symbols = Symbols.Symbols;
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Scpe_sig_raw = Scpe_sig_raw.Scpe_sig_raw;
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fsym = Symbols.fs;
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M = Symbols.logbook.ModifierCopy{1}.M;
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duob_mode = Symbols.logbook.ModifierCopy{1}.duobinary_mode;
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Scpe_sig_resampled = Scpe_sig_raw.resample("fs_in", Scpe_sig_raw.fs, "fs_out", 2*fsym);
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[~, Scpe_cell, ~, found_sync] = Scpe_sig_resampled.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
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else
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% Run quick Simulation
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tx_simulation;
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end
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% Handle Settings and argument replacement
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len_tr = 4096*2;
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ffe_order = [50, 5, 5];
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dfe_order = [0, 0, 0];
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pf_ncoeffs = 1;
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mu_ffe = [0.0001, 0.0008, 0.001];
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mu_dfe = 0.0004;
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mu_dc = 0.005;
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dc_buffer_len = 1;
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mu_tr = 0;
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mu_dd = 0.05;
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adaption= 1;
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use_dd_mode = 1;
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use_ffe = 1;
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use_dfe = 0;
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use_vnle_mlse = 0;
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use_dbtgt = 0;
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use_dbenc = 0;
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use_ml_mlse = 1;
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addProcessingResultToDatabase = 0;
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% Overwrite default parameters if given in options.parameters
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paramStruct = options.parameters;
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if ~isempty(paramStruct)
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paramNames = fieldnames(paramStruct);
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for i = 1:numel(paramNames)
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thisName = paramNames{i};
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thisValue = paramStruct.(thisName);
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eval([thisName ' = thisValue;']);
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end
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end
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% Configure equalizers
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options.max_occurences = min(options.max_occurences,length(Scpe_cell));
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for r = 1:options.max_occurences
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%FFE
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% eq_dfe = FFE("epochs_tr",5,"epochs_dd",2,"len_tr",2^13,"mu_dd",mu_dd,"mu_tr",mu_tr,"order",25,"sps",2,"decide",0, "adaption",adaption_method(adaption),"dd_mode",use_dd_mode);
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%
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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% mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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eq_post = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",1e-4,"mu_tr",0,"order",2001,"sps",1,"decide",0,"adaption_technique","lms");
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eq_post = FFE("epochs_tr",5,"epochs_dd",2,"len_tr",2^13,"mu_dd",mu_dd,"mu_tr",mu_tr,"order",25,"sps",2,"decide",0, "adaption",adaption_method(adaption),"dd_mode",use_dd_mode);
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% Duobinary signaling (db encoded)
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mlse_db_enc = MLSE("DIR", [1,1], "duobinary_output", 0, "M", M, "trellis_states", PAMmapper(M,0).levels);
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eq_db_enc = EQ("Ne", ffe_order, "Nb", dfe_order, "training_length", len_tr, ...
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"training_loops", 5, "dd_loops", 5, "K", 2, "DCmu", mu_dc, ...
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"DDmu", [mu_ffe mu_dfe], "DFEmu", 0.005, "FFEmu", 0, "plotfinal", 0, "ideal_dfe", 1);
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% Preprocess signal
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Scpe_sig = preprocessSignal(Scpe_cell{r}, Symbols, fsym);
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Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',-6);
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Scpe_sig.spectrum("fignum",201,"normalizeTo0dB",0,"displayname",'Rx');
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ylim([-30,3]);
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xlim([-5,100]);
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% Scpe_sig.spectrum("fignum",22233,"normalizeTo0dB",0,"displayname",'Rx');
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% Scpe_sig.eye(fsym,M,"fignum",1024);
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Scpe_sig.signal = Scpe_sig.signal(1:2*Symbols.length);
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Scpe_sig.signal = real(Scpe_sig.signal);
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if duob_mode ~= db_mode.db_encoded
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if use_ffe
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ffe_order = [50, 0, 0];
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eq_dfe = EQ("Ne",ffe_order,"Nb",[0,0,0],"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);
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ffe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits,...
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"precode_mode",duob_mode,...
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'showAnalysis',0,...
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"postFFE",[],...
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"eth_style_symbol_mapping",0);
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output.ffe_package{r} = ffe_results;
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ffe_results.metrics.print;
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ffe_results.config.equalizer_structure = "ffe";
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if options.append_to_db
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database.addProcessingResult(run_id, ffe_results.metrics, ffe_results.config);
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end
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end
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if use_dfe
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ffe_order = [50, 5, 5];
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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);
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dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits,...
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"precode_mode",duob_mode,...
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'showAnalysis',0,...
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"postFFE",[],...
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"eth_style_symbol_mapping",0);
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output.ffe_package{r} = dfe_results;
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dfe_results.config.equalizer_structure = "dfe";
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dfe_results.metrics.print;
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if options.append_to_db
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database.addProcessingResult(run_id, dfe_results.metrics, dfe_results.config);
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end
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end
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if use_vnle_mlse
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pf_ncoeffs = 1;
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ffe_order = [50, 5, 5];
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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",0);
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% eq_ = VNLE("epochs_tr",5,"epochs_dd",5,"len_tr",4096*2,"mu_dd",[0.0004 0.0005 0.0006],"mu_tr",0.0004,"order",[50,5,5],"sps",2,"decide",0);
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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useviterbi = 0;
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if useviterbi
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mlse_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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else
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if duob_mode == db_mode.no_db && M == 6 %only for PAM-6 and no duobinary precoding, otherwise leads to false sequence estimation
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trellexlusion = 1;
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else
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trellexlusion = 0;
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end
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%state_mode 3 -> stat lvl; state_mode 2 -> use target lvls
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%scale_mode 2 -> mmse adaption
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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',trellexlusion,'trellis_state_mode',2);
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end
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[ffe_results, mlse_results] = vnle_postfilter_mlse(eq_, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode,...
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'showAnalysis', 0, ...
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"postFFE", [],...
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"eth_style_symbol_mapping", 0);
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ffe_results.metrics.print;
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ffe_results.config.equalizer_structure = "vnle";
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mlse_results.metrics.print;
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output.mlse_package{r} = mlse_results;
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output.vnle_package{r} = ffe_results;
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if options.append_to_db
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database.addProcessingResult(run_id, mlse_results.metrics, mlse_results.config);
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database.addProcessingResult(run_id, ffe_results.metrics, ffe_results.config);
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end
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end
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if use_ml_mlse
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%ML-based MLSE (L=2)
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mu_ml = 0.01; training_epochs = 100;
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ml_mlse_equalizer = ML_MLSE("epochs_tr",training_epochs,"epochs_dd",1, ...
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"len_tr",length(Scpe_sig)/4,"mu_dd",mu_ml,"mu_tr",mu_ml,"order",11,"sps",2, ...
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"traceback_depth",128,"L",1,"delta",4,"adaptive_mu",0);
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[ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Scpe_sig, Symbols, Tx_bits,"precode_mode",duob_mode);
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output.mlmlse_package{r} = ml_mlse_results;
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if options.append_to_db
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database.addProcessingResult(run_id, ml_mlse_results.metrics, ml_mlse_results.config);
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end
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end
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if use_dbtgt
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useviterbi = 0;
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if useviterbi
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mlse_db_ = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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else
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if duob_mode == db_mode.no_db && M == 6 %only for PAM-6 and no duobinary precoding, otherwise leads to false sequence estimation
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trellexlusion = 1;
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else
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trellexlusion = 0;
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end
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mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels,'scale_mode',2,'trellis_exclusion',trellexlusion,'trellis_state_mode',3);
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end
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ffe_order = [50, 5, 5];
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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);
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dbt_results = duobinary_target(eq_, mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode, ...
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'showAnalysis', 0,...
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"postFFE", []);
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dbt_results.metrics.print;
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output.dbtgt_package{r} = dbt_results;
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if options.append_to_db
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database.addProcessingResult(run_id, dbt_results.metrics, dbt_results.config);
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end
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end
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end
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if duob_mode == db_mode.db_encoded
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mlse_db_enc = MLSE_viterbi("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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mlse_db_enc = MLSE("DIR", [1,1], "duobinary_output", 0, "M", M, "trellis_states", PAMmapper(M,0).levels);
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db_results = duobinary_signaling(eq_db_enc, mlse_db_enc, M, Scpe_sig, Symbols, Tx_bits, "precode_mode",duob_mode, "showAnalysis",0,"postFFE",[]);
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output.dbenc_package{r} = db_results;
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if options.append_to_db
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database.addProcessingResult(run_id, db_results.metrics, db_results.config);
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end
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end
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end
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catch ME
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save('workerError.mat','ME');
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rethrow(ME);
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end
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end |