Many changes towards simulation of JLT and once again the evaluation of the Highspeed data from Lab experiments 2024
This commit is contained in:
Silas Oettinghaus
@@ -5,9 +5,11 @@ arguments
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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_path
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options.database_name
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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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% Initialize output structures
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@@ -17,34 +19,72 @@ output.vnle_package = {};
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output.dbtgt_package = {};
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output.dbenc_package = {};
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% Initialize database connection
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database = DBHandler("pathToDB", [options.database_path, options.database_name], "type", "sqlite");
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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(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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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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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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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 = 0.00;
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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 = 1;
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use_vnle_mlse = 1;
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use_dbtgt = 1;
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use_dbenc = 0;
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use_dbenc = 1;
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addProcessingResultToDatabase = 0;
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@@ -60,74 +100,148 @@ if ~isempty(paramStruct)
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end
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% Configure equalizers
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eq_lin = EQ("Ne",[50,0,0],"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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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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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_db_ = MLSE_viterbi("DIR",[1,1],"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);
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% Duobinary signaling (db encoded)
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mlse_db_enc = MLSE_viterbi("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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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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% Load signal data
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[Tx_bits, Symbols, Scpe_cell, ~] = loadSignalData(dataTable, options);
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%
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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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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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mlse_db_ = MLSE("DIR",[1,1],"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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% 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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for r = 1:numel(Scpe_cell)
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% Preprocess signal
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Scpe_sig = preprocessSignal(Scpe_cell{r}, Symbols, fsym);
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if duob_mode ~= db_mode.db_encoded
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if use_ffe
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ffe_results = ffe(eq_lin,M,Scpe_sig,Symbols,Tx_bits,...
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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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dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits,...
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"precode_mode",duob_mode,...
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'showAnalysis',1,...
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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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output.ffe_package{r} = dfe_results;
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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, ffe_results.metrics, ffe_results.config);
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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_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.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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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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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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[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', 1, ...
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"postFFE", [],...
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"eth_style_symbol_mapping", 0);
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output.mlse_package{r} = mlse_results;
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output.vnle_package{r} = ffe_results;
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ffe_results.metrics.print;
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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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pf_ncoeffs = 2;
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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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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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[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', 1, ...
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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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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_dbtgt
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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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output.dbtgt_package{r} = dbt_results;
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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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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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@@ -36,20 +36,21 @@ if ~isempty(options.postFFE)
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end
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% Process through MLSE
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eq_signal = mlse_.process(eq_signal);
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% [mlse_signal] = mlse_.process(eq_signal);
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[mlse_signal,~,GMI_MLSE] = mlse_.process(eq_signal,tx_symbols);
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% Apply duobinary encoding and decoding
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eq_signal = Duobinary().encode(eq_signal);
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eq_signal = Duobinary().decode(eq_signal);
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mlse_signal = Duobinary().encode(mlse_signal);
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mlse_signal = Duobinary().decode(mlse_signal);
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% Demap symbols to bits
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rx_bits = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).demap(eq_signal);
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rx_bits = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).demap(mlse_signal);
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%% Calculate BER and metrics
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[bits_db, errors_db, ber_db, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 100, "skip_end", 150, "returnErrorLocation", 1);
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% Calculate performance metrics
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[snr, snr_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
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% Calculate performance metrics after duobinary FFE!
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[snr, snr_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal); %SNR of duobinary sequence - not directly comparable to
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[gmi] = calc_air(eq_signal, tx_symbols, "skip_front", 10000, "skip_end", 10000);
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air = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi ./ log2(double(M));
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[evm_total, evm_lvl] = calc_evm(eq_signal, tx_symbols);
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@@ -23,8 +23,8 @@ if ~isempty(options.postFFE)
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end
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mlse_.DIR = [1,1];
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mlse_sig_sd = mlse_.process(eq_signal);
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% mlse_sig_sd = mlse_.process(eq_signal);
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[mlse_sig_sd,LLR,GMI_MLSE] = mlse_.process(eq_signal,tx_symbols);
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mlse_sig_hd = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
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% precoding to mitigate error propagation, most prominently used in
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@@ -73,6 +73,10 @@ end
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rx_bits = PAMmapper(M,0,"eth_style",options.eth_style_symbol_mapping).demap(mlse_sig_hd);
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[bits_db,errors_db,ber_db,errorIndice_db] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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alpha = arburg(eq_noise.signal,1);%pf_.coefficients(2);
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alpha = alpha(2);
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gmi_mlse = GMI_MLSE;
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air_mlse = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi_mlse ./ log2(double(M));
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db_results = struct();
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db_results.metrics = Metricstruct;
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@@ -85,13 +89,10 @@ db_results.metrics.numBits = bits_db;
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db_results.metrics.numBitErr = errors_db;
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db_results.metrics.BER_precoded = ber_db_diff_precoded;
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db_results.metrics.numBitErr_precoded = errors_db_diff_precoded;
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db_results.metrics.SNR = NaN;
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db_results.metrics.SNR_level = NaN;
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db_results.metrics.GMI = NaN;
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db_results.metrics.AIR = NaN;
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db_results.metrics.EVM = NaN;
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db_results.metrics.EVM_level = NaN;
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db_results.metrics.GMI = gmi_mlse;
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db_results.metrics.AIR = air_mlse;
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db_results.metrics.MLSE_dir = mlse_.DIR;
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db_results.metrics.Alpha = alpha;
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% Create DB results structure
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db_results.config = Equalizerstruct();
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@@ -99,7 +100,7 @@ eq_.e = [];
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eq_.e2 = [];
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eq_.e3 = [];
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db_results.config.eq = jsonencode(eq_);
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mlse_.DIR = [];
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% mlse_.DIR = [];
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db_results.config.mlse = jsonencode(mlse_);
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db_results.config.equalizer_structure = int32(equalizer_structure.vnle_db_mlse);
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db_results.config.comment = 'function: Duobinary tgt. (VNLE -> MLSE)';
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@@ -36,6 +36,11 @@ if ~isempty(options.postFFE)
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toc
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end
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try
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ch_coefficients = arburg(eq_noise.signal,1);
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channel_alpha = ch_coefficients(2);
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end
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% Hard decision on FFE output
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eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
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@@ -66,10 +71,15 @@ end
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% Create FFE results structure
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ffe_results = struct();
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try
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eq_.e = [];
|
||||
eq_.e2 = [];
|
||||
eq_.e3 = [];
|
||||
eq_.b = [];
|
||||
eq_.b2 = [];
|
||||
eq_.b3 = [];
|
||||
end
|
||||
|
||||
eq_.e = [];
|
||||
eq_.e2 = [];
|
||||
eq_.e3 = [];
|
||||
ffe_results.config = Equalizerstruct();
|
||||
ffe_results.config.eq = jsonencode(eq_);
|
||||
ffe_results.config.equalizer_structure = int32(equalizer_structure.ffe);
|
||||
@@ -95,7 +105,7 @@ ffe_results.metrics.GMI = gmi;
|
||||
ffe_results.metrics.AIR = air;
|
||||
ffe_results.metrics.EVM = evm_total;
|
||||
ffe_results.metrics.EVM_level = evm_lvl;
|
||||
|
||||
ffe_results.metrics.Alpha = channel_alpha;
|
||||
|
||||
|
||||
end
|
||||
@@ -140,24 +150,40 @@ end
|
||||
end
|
||||
|
||||
function displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, tx_symbols, M, postFFE)
|
||||
% Display analysis plots and metrics
|
||||
figure(336);
|
||||
showEQNoisePSD(eq_noise, "fignum", 336, "displayname", 'Residual Noise after FFE');
|
||||
% Display analysis plots and metrics
|
||||
|
||||
if ~isempty(postFFE)
|
||||
showEQcoefficients('n1', postFFE.e, "displayname", 'Coefficients', 'fignum', 338);
|
||||
end
|
||||
% Initialize figure handles
|
||||
% Corrected line - added tx_symbols as second positional argument
|
||||
showLevelScatter(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols, "fignum", 100);
|
||||
|
||||
showEQfilter(eq_.e, eq_signal_sd.fs.*2);
|
||||
warning off
|
||||
showLevelScatter(eq_signal_sd, tx_symbols, "fignum", 101);
|
||||
figure(gcf);hold on; plot(((1:length(eq_noise.signal)) / eq_noise.fs) * 1e6,movmean(eq_noise.signal,2000,1), 'LineWidth',3,'Color','black')
|
||||
warning on
|
||||
|
||||
figure(341); clf;
|
||||
showLevelHistogram(eq_signal_sd, tx_symbols, "fignum", 341);
|
||||
showLevelHistogram(eq_signal_sd, tx_symbols, "fignum", 102);
|
||||
|
||||
warning off
|
||||
figure(400); clf;
|
||||
showLevelScatter(eq_signal_sd, tx_symbols, "fignum", 400);
|
||||
showEQNoisePSD(eq_noise, "fignum", 103, "displayname", 'Residual Noise after FFE');
|
||||
|
||||
% Figure 2: Post-FFE coefficients (if available)
|
||||
if ~isempty(postFFE)
|
||||
showEQcoefficients('n1', postFFE.e, "displayname", 'Coefficients', 'fignum', 104);
|
||||
end
|
||||
|
||||
try
|
||||
figure(339);
|
||||
showEQfilter(eq_.e_tr, eq_signal_sd.fs.*2,"displayname",'training','fignum',339);
|
||||
showEQfilter(eq_.e, eq_signal_sd.fs.*2,"displayname",'dec. directed','fignum',339);
|
||||
legend on
|
||||
end
|
||||
|
||||
try
|
||||
figure(240); hold on; plot(pow2db(movmean(eq_.debug_struct.error_tr',100)));ylim([-30,3]);title('error training');
|
||||
|
||||
figure(241); hold on; plot(pow2db(movmean(eq_.debug_struct.update_tr',100)));title('update step training');
|
||||
|
||||
figure(242); hold on; plot(pow2db(movmean(eq_.debug_struct.update',1000)));title('update step dd');
|
||||
end
|
||||
% eq_signal_sd.eye(eq_signal_sd.fs,M,"displayname",'Eye','fignum',105);
|
||||
|
||||
figure(401); clf;
|
||||
showLevelScatter(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols, "fignum", 401);
|
||||
warning on
|
||||
end
|
||||
@@ -45,9 +45,10 @@ end
|
||||
eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
|
||||
|
||||
% Process through postfilter and MLSE
|
||||
mlse_sig_sd = pf_.process(eq_signal_sd, eq_noise);
|
||||
[mlse_sig_sd,whitened_noise] = pf_.process(eq_signal_sd, eq_noise);
|
||||
mlse_.DIR = pf_.coefficients;
|
||||
mlse_sig_sd = mlse_.process(mlse_sig_sd);
|
||||
|
||||
[mlse_sig_sd,LLR,GMI_MLSE] = mlse_.process(mlse_sig_sd,tx_symbols);
|
||||
mlse_sig_hd = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).quantize(mlse_sig_sd);
|
||||
|
||||
%% Calculate BER based on precoding mode
|
||||
@@ -63,7 +64,17 @@ air_vnle = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi_vnle ./ log2(dou
|
||||
[std_rxraw_total, std_rxraw_lvl] = calc_std(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols);
|
||||
|
||||
% MLSE metrics
|
||||
alpha = pf_.coefficients(2);
|
||||
alpha = arburg(eq_noise.signal,1);%pf_.coefficients(2);
|
||||
alpha = alpha(2);
|
||||
gmi_mlse = GMI_MLSE;
|
||||
air_mlse = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi_mlse ./ log2(double(M));
|
||||
|
||||
%% Display analysis if requested
|
||||
if options.showAnalysis
|
||||
displayAnalysis(eq_noise,whitened_noise, eq_signal_sd, rx_signal, eq_, pf_, mlse_, tx_symbols, M, options.postFFE);
|
||||
end
|
||||
|
||||
|
||||
|
||||
%% Prepare output structures
|
||||
% Determine postFFE order
|
||||
@@ -94,19 +105,21 @@ ffe_results.metrics.GMI = gmi_vnle;
|
||||
ffe_results.metrics.AIR = air_vnle;
|
||||
ffe_results.metrics.EVM = evm_vnle_total;
|
||||
ffe_results.metrics.EVM_level = evm_vnle_lvl;
|
||||
ffe_results.metrics.Alpha = [];
|
||||
ffe_results.metrics.Alpha = alpha;
|
||||
|
||||
try
|
||||
eq_.e = [];
|
||||
eq_.e2 = [];
|
||||
eq_.e3 = [];
|
||||
end
|
||||
|
||||
% Create FFE results structure
|
||||
|
||||
eq_.e = [];
|
||||
eq_.e2 = [];
|
||||
eq_.e3 = [];
|
||||
ffe_results.config = Equalizerstruct();
|
||||
ffe_results.config.eq = jsonencode(eq_);
|
||||
ffe_results.config.equalizer_structure = int32(equalizer_structure.vnle);
|
||||
ffe_results.config.comment = 'function: vnle_postfilter_mlse - FFE part';
|
||||
|
||||
|
||||
|
||||
mlse_results = struct();
|
||||
mlse_results.metrics = Metricstruct;
|
||||
mlse_results.metrics.result_id = NaN;
|
||||
@@ -118,12 +131,11 @@ mlse_results.metrics.numBits = numbits.mlse;
|
||||
mlse_results.metrics.numBitErr = errors.mlse;
|
||||
mlse_results.metrics.BER_precoded = bers.mlse_precoded;
|
||||
mlse_results.metrics.numBitErr_precoded = errors.mlse_precoded;
|
||||
mlse_results.metrics.SNR = NaN;
|
||||
mlse_results.metrics.SNR_level = NaN;
|
||||
mlse_results.metrics.GMI = NaN;
|
||||
mlse_results.metrics.AIR = NaN;
|
||||
mlse_results.metrics.EVM = NaN;
|
||||
mlse_results.metrics.EVM_level = NaN;
|
||||
% mlse_results.metrics.SNR = NaN;
|
||||
mlse_results.metrics.GMI = gmi_mlse;
|
||||
mlse_results.metrics.AIR = air_mlse;
|
||||
% mlse_results.metrics.EVM = NaN;
|
||||
% mlse_results.metrics.EVM_level = NaN;
|
||||
mlse_results.metrics.Alpha = alpha;
|
||||
mlse_results.metrics.MLSE_dir = mlse_.DIR;
|
||||
|
||||
@@ -131,15 +143,12 @@ mlse_results.metrics.MLSE_dir = mlse_.DIR;
|
||||
|
||||
mlse_results.config = Equalizerstruct();
|
||||
mlse_results.config.eq = jsonencode(eq_);
|
||||
mlse_.DIR = [];
|
||||
mlse_.DIR = length(mlse_.DIR)-1;
|
||||
mlse_results.config.mlse = jsonencode(mlse_);
|
||||
mlse_results.config.equalizer_structure = int32(equalizer_structure.vnle_pf_mlse);
|
||||
mlse_results.config.comment = 'function: vnle_postfilter_mlse - MLSE part';
|
||||
|
||||
%% Display analysis if requested
|
||||
if options.showAnalysis
|
||||
displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, pf_, mlse_, tx_symbols, M, options.postFFE);
|
||||
end
|
||||
|
||||
|
||||
end
|
||||
|
||||
@@ -206,7 +215,7 @@ end
|
||||
end
|
||||
|
||||
|
||||
function displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, pf_, mlse_, tx_symbols, M, postFFE)
|
||||
function displayAnalysis(eq_noise, whitened_noise, eq_signal_sd, rx_signal, eq_, pf_, mlse_, tx_symbols, M, postFFE)
|
||||
% Display analysis plots and metrics
|
||||
figure(336);
|
||||
showEQNoisePSD(eq_noise, "fignum", 336, "displayname", 'Residual Noise after VNLE', 'postfilter_taps', pf_.coefficients);
|
||||
@@ -228,4 +237,9 @@ showLevelScatter(eq_signal_sd, tx_symbols, "fignum", 400);
|
||||
showLevelScatter(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols, "fignum", 401);
|
||||
drawnow;
|
||||
warning on
|
||||
|
||||
|
||||
whitened_noise.spectrum("displayname",'after postfilter','fignum',342);
|
||||
eq_noise.spectrum("displayname",'before postfilter','fignum',342);
|
||||
|
||||
end
|
||||
Reference in New Issue
Block a user