172 lines
7.4 KiB
Matlab
172 lines
7.4 KiB
Matlab
% function [ber] = imdd_labdata_example(varargin)
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% TX
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M = 4;
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fsym = 224e9;
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f_nyquist = fsym/2;
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apply_pulsef = 0;
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fdac = 2*fsym;%256e9;
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fadc = 2*fsym;%256e9;
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fdac = 256e9;
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fadc = 256e9;
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random_key = 1;
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db_precode = 1;
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db_encode = 0;
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rcalpha = 0.05;
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kover = 16;
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vbias_rel = 0.5;
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u_pi = 2.9;
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vbias = -vbias_rel*u_pi;
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laser_wavelength = 1293;
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laser_linewidth = 0;
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tx_bw_nyquist = 1.5;
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% Channel
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link_length = 0;
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% RX
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rop = -7.5;
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rx_bw_nyquist = 1.5;
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% EQ
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eq_mode = equalizer_structure.vnle_pf_mlse;
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ffe_order=[50,0,0];
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vnle_order=[50,7,7];
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dfe_order = [0 0 0];
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len_tr = 4096*2;
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mu_ffe = [0.0004 0.0004 0.0004];
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mu_dfe = 0.0004;
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mu_dc = 0.05;
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dfe_ = sum(dfe_order)>0;
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%
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% % Parse optional input arguments
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% if ~isempty(varargin)
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% var_s = varargin{1};
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% if isstruct(var_s)
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% fields = fieldnames(var_s);
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% for i = 1:numel(fields)
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% eval([fields{i}, ' = ', num2str( var_s.(fields{i}) ), ';']);
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% fprintf("%s <-- %.2f \n", fields{i}, var_s.(fields{i}));
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% end
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% else
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% error('Optional variables should be passed as a struct.');
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% end
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% end
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basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
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useGui = 0;
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db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
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filterParams = db.tables;
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% filterParams.Runs.run_id = 2958; % no db
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% filterParams.Runs.run_id = 2937; % no db
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filterParams.Configurations = struct( ...
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'bitrate', 300e9, ...
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'db_mode', 0, ...
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'fiber_length', 1, ...
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'interference_attenuation', [], ...
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'interference_path_length', [], ...
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'is_mpi', 0, ...
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'pam_level', 4, ...
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'precomp_amp', [], ...
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'rop_attenuation', 0, ...
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'symbolrate', [], ...
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'v_awg', [], ...
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'v_bias', [], ...
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'wavelength', 1310 ...
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);
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selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
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'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','BERs.ber'};
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[dataTable,sql_query] = db.queryDB(filterParams, selectedFields);
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[~, uniqueIdx] = unique(dataTable.run_id); % Get unique run_id indices
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dataTable = dataTable(uniqueIdx,:); % Extract unique configurations for each run_id
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fprintf('Found %d entries for requested Configuration. IDs are: %s \n \n',size(dataTable,1),jsonencode(dataTable.run_id(1:min(size(dataTable,1),100))));
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tx_bits = load([basePath, char(dataTable.tx_bits_path(1))]);
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tx_bits = tx_bits.Bits;
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tx_symbols = load([basePath, char(dataTable.tx_symbols_path(1))]);
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tx_symbols = tx_symbols.Symbols;
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rx_sync = load([basePath, char(dataTable.rx_sync_path(1))]);
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rx_sync = rx_sync.S;
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fsym = tx_symbols.fs;
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%%%%%% Sample to 2x fsym %%%%%%
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Scpe_sig = rx_sync{1}.resample("fs_in",rx_sync{1}.fs,"fs_out",2*fsym);
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%%%%%% Sync Rx signal with reference %%%%%%
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[Scpe_sig,S] = Scpe_sig.tsynch("reference",tx_symbols,"fs_ref",fsym);
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Scpe_sig.spectrum("displayname",'Rx (Scpe+Sync+Resample)','fignum',100,'normalizeTo0dB',0);
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Scpe_sig = Filter('filtdegree',4,"f_cutoff",tx_symbols.fs.*0.6,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
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Scpe_sig.spectrum("displayname",'Rx (Scpe+Sync+Resample+LPF)','fignum',100,'normalizeTo0dB',0);
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%%% EQUALIZING
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ber = struct();
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switch eq_mode
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case equalizer_structure.ffe
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%FFE
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if db_precode
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Bits_ = PAMmapper(M,0).demap(Symbols);
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else
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Bits_ = Bits;
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end
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eq_ffe = 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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eq_ffe = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0);
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eq_ffe = FFE_DCremoval("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0,"dc_buffer_len",512,"mu_dc",0.05);
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[eq_sig,eq_noise,ber.ber_ffe,totalErrors] = vnle( eq_ffe,M,Scpe_sig ,Symbols, Bits_);
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eq_noise.spectrum("displayname",'Noise Spectrum after FFE','fignum',41,'normalizeTo0dB',0);
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case equalizer_structure.vnle
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%VNLE
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eq_vnle = EQ("Ne",vnle_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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[eq_sig,eq_noise,ber.ber_vnle,totalErrors] = vnle(eq_vnle,M,Scpe_sig ,Symbols, Bits_);
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eq_noise.spectrum("displayname",'Noise Spectrum after VNLE','fignum',41,'normalizeTo0dB',0);
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case equalizer_structure.vnle_pf_mlse
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%VNLE + PF + MLSE
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eq_mlse = EQ("Ne",vnle_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",1);
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mlse_ = MLSE("DIR",[0,0],"duobinary_output",0,"M",[],"trellis_states",[]);
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[eq_sig,eq_noise,ber.ber_mlse,totalErrors] = vnle_postfilter_mlse(eq_mlse , pf_, mlse_,M, Scpe_sig ,Symbols, Bits_);
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pf_.showFilter(eq_noise);
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eq_noise.spectrum("displayname",'Noise Spectrum after VNLE+PF','fignum',41,'normalizeTo0dB',0);
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case equalizer_structure.db_precoded
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%EQ targets DB => less precompensation; pre-coded
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mlse_db_pre = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels);
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eq_db_pre = EQ("Ne",vnle_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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[eq_sig,eq_noise,ber.ber_db,totalErrors] = duobinary_target(eq_db_pre, mlse_db_pre,M, Scpe_sig ,Symbols, Bits);
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eq_noise.spectrum("displayname",'Noise Spectrum after DB','fignum',41,'normalizeTo0dB',0);
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%->append BER to DB
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case equalizer_structure.db_encoded
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%db signaling => db encoded
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mlse_db_enc = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels);
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eq_db_enc = EQ("Ne",vnle_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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[eq_sig,eq_noise,ber.ber_db_enc,totalErrors] = duobinary_signaling(eq_db_enc, mlse_db_enc,M, Scpe_sig ,Symbols, Bits);
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%->append BER to DB
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end
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fprintf('BER FFE: %.2e \n',ber.ber_mlse);
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% % El_sig.spectrum("displayname",'Tx Spectrum','fignum',10,'normalizeTo0dB',1);
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% Scpe_sig.spectrum("displayname",'Rx Spectrum','fignum',100,'normalizeTo0dB',1);
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% end |