92 lines
3.4 KiB
Matlab
92 lines
3.4 KiB
Matlab
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% Get the script folder
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scriptFolder = fileparts(mfilename('fullpath'));
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% Find the HDF5 file in the folder
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files = dir(fullfile(scriptFolder, '*.h5'));
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if isempty(files)
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error('No HDF5 files found in the script folder.');
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end
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% Select the first matching file (modify as needed)
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filename = files(6).name;
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% filename = 'Pmod_8p0023dBm_P_PD_6p4776dBm_W03C34-0409E03_64GBd_2PAM__20250218T181323.h5';
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% Extract parameters from the filename using an updated regex
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tokens = regexp(filename, 'Pmod_([-0-9p]+)dBm_P_PD_([-0-9p]+)dBm_.*?_(\d+)GBd_(\d+)PAM__\d+T\d+', 'tokens');
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if isempty(tokens)
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error('Filename format not recognized.');
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end
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tokens = tokens{1};
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% Convert values
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P_laser = str2double(strrep(tokens{1}, 'p', '.'));
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P_pd = str2double(strrep(tokens{2}, 'p', '.'));
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fsym = str2double(tokens{3}) * 1e9; % Convert GBd to Hz
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M = str2double(tokens{4});
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% Display results
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fprintf('Loaded file: %s\n', filename);
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fprintf('P_laser: %.3f dBm\n', P_laser);
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fprintf('P_pd: %.3f dBm\n', P_pd);
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fprintf('fsym: %.3f Hz\n', fsym);
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fprintf('M: %d\n', M);
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%%% Load Data
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folder = "/Users/silasoettinghaus/Documents/MATLAB/imdd_simulation/projects/Messung_Zürich";
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filepath = fullfile(folder,filename);
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ief_ = h5info(filepath);
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fs_rx = h5readatt(filepath,'/','fs'); %sampling frequency at Rx
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fs_tx = h5readatt(filepath, '/','fs_Tx'); %sampling frequency at Tx
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fsym = h5readatt(filepath, '/','R'); %Baudrate
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M = h5readatt(filepath, '/','M'); % PAM- 'M'
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ROF = h5readatt(filepath, '/','ROF');
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PulseShape =h5readatt(filepath, '/','PulseShape');
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yOrg = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YOrg');
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yInc = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YInc');
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plotDisplayName = sprintf('P_{cw} = %.3f dBm, P_{PD} = %.3f dBm, f_{sym} = %.3f GBd, M = %d', ...
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P_laser, P_pd, fsym / 1e9, M);
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dataRx = double(h5read(filepath, '/Waveforms/Channel 2/Channel 2Data')); % rohdaten des CH4
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bitsTx = h5read(filepath, '/Settings/dataTx'); %Binär
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bitsTx = reshape(bitsTx,log2(M),[])';
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%%% Build Tx Signal (Bits, Pam Map, Symbols)
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Tx_bits = Informationsignal(bitsTx);
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Tx_symbols = PAMmapper(M,0,"eth_style",1).map(Tx_bits);
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Tx_symbols.fs = fsym;
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% Tx_symbols.plot("fignum",1,"displayname",'Rx Signal');
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% Tx_symbols.move_it_spectrum("fignum",2,"displayname",'tx spectrum');
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% Tx_symbols.spectrum("fignum",3,"displayname",'Rx Signal','normalizeTo0dB',0);
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%%% Build Rx Signal (Rx, normalize,remove mean)
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dataRx = dataRx*yInc+yOrg;
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Rx_Sig = Informationsignal(dataRx,"fs",fs_rx);
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Rx_Sig = Rx_Sig.normalize("mode","rms");
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% Rx_Sig.power();
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% Rx_Sig.eye(fsym,M,"fignum",4,"displayname",'eye diagram');
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% Rx_Sig.plot("fignum",5,"displayname",'Rx Signal');
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% Rx_Sig.move_it_spectrum("fignum",6,"displayname",'tx spectrum');
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Rx_Sig.spectrum("fignum",3,"displayname",'Rx Signal','normalizeTo0dB',0);
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%%%%%% Sample to 2x fsym %%%%%%
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Rx_Sig_resamp = Rx_Sig.resample("fs_out",2*fsym);
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%%%%%% Sync Rx signal with reference (S is a cell array with all occurences) %%%%%%
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[Rx_Sig_sync,S,isFlipped] = Rx_Sig_resamp.tsynch("reference",Tx_symbols,"fs_ref",fsym,"debug_plots",0);
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eq_vnle_dfe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",1,"ideal_dfe",0);
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[result] = vnle(eq_vnle_dfe,M,Rx_Sig_sync,Tx_symbols,Tx_bits,"precode_mode",db_mode.no_db,"showAnalysis",1,'eth_style',1);
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