239 lines
8.2 KiB
Matlab
239 lines
8.2 KiB
Matlab
function [output] = imdd_model(varargin)
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simulation_mode = 1;
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%%% Change folder
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curFolder = pwd;
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funcFolder=fileparts(mfilename('fullpath'));
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if ~isempty(funcFolder)
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cd(funcFolder);
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end
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%%% Run parameters
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% TX
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M = 4;
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fsym = 180e9;
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apply_pulsef = 1;
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fdac = 256e9;
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fadc = 256e9;
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random_key = 1;
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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 = 3;
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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 = 0.8;
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% Channel
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link_length = 1;
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% RX
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rop = -8;
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rx_bw_nyquist = 0.8;
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vnle_order1 = 50;
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vnle_order2 = 7;
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vnle_order3 = 7;
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vnle_order=[vnle_order1,vnle_order2,vnle_order3];
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dfe_order = [0 0 0];
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pf_ncoeffs = 1;
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alpha = 0;
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len_tr = 4096*2;
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mu_ffe1 = 0.0001;
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mu_ffe2 = 0.0008;
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mu_ffe3 = 0.001;
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mu_dc = 0.005;
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% mu_dc = 0;
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mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
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mu_dfe = 0.0004;
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dfe_ = sum(dfe_order)>0;
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% duob_mode = db_mode.no_db;
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%%% change specific parameter if given in varargin
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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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if isnumeric(fields{i})
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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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else
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eval([fields{i}, ' = ', 'var_s.(fields{',num2str(i),'})' , ';']);
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end
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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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fsym_ = floor( bitrate*1e-9./log2(M) ).*1e9;
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if fsym_ ~= fsym
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fsym = fsym_;
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% fprintf('Adapted symbolrate to %d GBd, to match provided bitrate of %d GBit/s using PAM %d \n',fsym.*1e-9,bitrate.*1e-9, M);
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end
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f_nyquist = fsym/2;
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Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
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[Digi_sig,Symbols,Tx_bits] = PAMsource(...
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"fsym",fsym,"M",M,"order",18,"useprbs",0,...
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"fs_out",fdac,...
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"applyclipping",0,"clipfactor",1.5,...
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"applypulseform",apply_pulsef,"pulseformer",Pform,...
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"randkey",random_key,...
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'duobinary_mode',duob_mode,...
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"mrds_code",0,"mrds_blocklength",512).process();
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Digi_sig.spectrum("displayname",'Digi Spectrum','fignum',10,'normalizeTo0dB',1);
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%%%%% AWG
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% El_sig = M8199A("kover",kover).process(Digi_sig);
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El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
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% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',0);
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% El_sig = El_sig.setPower(0,"dBm");
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%%%%% Low-pass el. components %%%%%%
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tx_bwl = tx_bw_nyquist.*f_nyquist;
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% tx_bwl = 80e9;
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El_sig = Filter('filtdegree',4,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
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% El_sig.spectrum("displayname",'Digi Spectrum','fignum',100,'normalizeTo0dB',1);
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%%%%% Electrical Driver Amplifier %%%%%%
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% El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
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El_sig = El_sig.normalize("mode","oneone");
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scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2));
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El_sig = El_sig .* scaling;
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%%%%% MODULATE E/O CONVERSION %%%%%%
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[Opt_sig] = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs,"lambda",laser_wavelength,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",random_key+1,"alpha",alpha).process(El_sig);
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% Opt_sig.spectrum("displayname",'Opt Spectrum','fignum',10,'normalizeTo0dB',1);
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Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.07).process(Opt_sig);
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%%%%%% ROP %%%%%%
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Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
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%%%%%% PD Square Law %%%%%%
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Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11).process(Rx_sig);
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%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
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rx_bwl = rx_bw_nyquist.*f_nyquist;
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% rx_bwl = 80e9;
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Rx_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
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% %%%%%% Low-pass Scope %%%%%%
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Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
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% Rx_sig.spectrum("displayname",'Analog Rx Spectrum','fignum',100,'normalizeTo0dB',1);
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%%%%%% Scope %%%%%%
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Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
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"delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
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"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
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"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(Rx_sig);
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output = struct();
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%%%%%% Sample to 2x fsym %%%%%%
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Scpe_sig = Scpe_sig.resample("fs_out",2*fsym);
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Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
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%%%%%% Sync Rx signal with reference %%%%%%
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[Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
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Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
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Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
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%%% EQUALIZING
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if 0
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% -------------------- FFE --------------------
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ffe_order = [50, 0, 0];
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eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0], ...
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"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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% % -------------------- FFE --------------------
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% ffe_order = [50, 0, 0];
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% eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0], ...
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% "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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% "K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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% "FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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%
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% output.ffe_results = ffe(eq_ffe,M,Scpe_sig,Symbols,Tx_bits, ...
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% "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
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% "eth_style_symbol_mapping",0);
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%
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% output.ffe_results.metrics.print
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% % -------------------- DFE --------------------
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% eq_dfe = EQ("Ne",ffe_order,"Nb",[2,0,0], ...
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% "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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% "K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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% "FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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%
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% output.dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits, ...
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% "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
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% "eth_style_symbol_mapping",0);
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%
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% output.dfe_results.metrics.print("description",'DFE');
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% % -------------------- VNLE + MLSE --------------------
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% pf_ncoeffs = 1;
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% ffe_order3 = [200, 0, 0];
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% eq_v = EQ("Ne",ffe_order3,"Nb",dfe_order, ...
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% "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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% "K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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% "FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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%
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% mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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%
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% [output.vnle_results, output.mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
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% "precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [], "eth_style_symbol_mapping", 0);
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% -------------------- DB target --------------------
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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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ffe_order = [50, 0, 0];
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eq_ = EQ("Ne",ffe_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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output.dbt_results = duobinary_target(eq_,mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [], "decoding_mode", decoding_mode);
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output.dbt_results.metrics.print("description",'Duobinary');
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disp('- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ')
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fprintf('\n')
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end |