175 lines
6.5 KiB
Matlab
175 lines
6.5 KiB
Matlab
function [ber] = imdd_simulation_minimal(varargin)
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% BASIC IMDD Model...
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% varargin is either empty or a struct, i.e.:
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% optionalvars = struct('bitrate',300e9,'M',6);
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% then:
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% imdd_simulation_minimal(optionalvars)
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% replaces the respective variables -> nice for looping parameter sets
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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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% TX
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M = 4;
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fsym = 112e9;
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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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db_precode = 0;
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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 = 1310;
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laser_linewidth = 0;
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tx_bw_nyquist = 0.95;
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% Channel
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link_length = 1; %km
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% RX
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rop = -7;
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rx_bw_nyquist = 0.9;
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% EQ
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vnle_order=[50,7,7];
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dfe_order = [2 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 = 0.00;
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% Replace optional input arguments if there are any
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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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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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%%%% TX Signal
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Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"rrcalpha",rcalpha);
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[Digi_sig,Tx_symbols,Tx_bits] = PAMsource(...
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"fsym",fsym,"M",M,"order",18,"useprbs",1,...
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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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"db_precode",db_precode,"db_encode",db_encode,...
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"mrds_code",0,"mrds_blocklength",512).process();
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Digi_sig.spectrum("displayname",'Digital Spectrum at TX','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",1,"kover",kover,"bit_resolution",12).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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El_sig.eye(fsym,M,"fignum",11,'displayname','Rx Eye');
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%%%%% Low-pass el. components %%%%%%
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El_sig = Filter('filtdegree',4,"f_cutoff",75e9,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
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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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%%%%% 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).process(El_sig);
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%%%%%% Fiber %%%%%%
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Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",link_length/1000,"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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Rx_sig.eye(fsym,M,"fignum",30,'displayname','Rx Eye');
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%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
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Rx_sig = Filter('filtdegree',4,"f_cutoff",75e9,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
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%%%%%% Low-pass inside Scope %%%%%%
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Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
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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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Scpe_sig.spectrum("displayname",'Digital (256 GSa/s) Rx Spectrum','fignum',10,'normalizeTo0dB',1);
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Scpe_sig.normalize("mode","rms").plot("displayname",'Digital (256 GSa/s) Rx Spectrum','fignum',21,'clear',1);
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%%%%%% Sample to 2x fsym %%%%%%
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Scpe_sig = Scpe_sig.resample("fs_in",fadc,"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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%%% EQUALIZING
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%FFE or VNLE
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[Eq_signal,Eq_noise] = 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).process(Scpe_sig,Tx_symbols);
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Rx_bits = PAMmapper(M,0).demap(Eq_signal);
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[~,numErrors,ber,~] = calc_ber(Rx_bits.signal,Tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
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Eq_signal.normalize("mode","rms").plot("displayname",'Digital (256 GSa/s) Rx Spectrum','fignum',21,'clear',0);
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%%% Visualize EQ Stuff
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figure(40);
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clf
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title(sprintf('PAM %d after EQ ; BER: %1.2e',M, ber ));
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constellation = unique(Tx_symbols.signal);
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received = NaN(numel(constellation),length(Tx_symbols));
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for lvl = 1:numel(constellation)
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%Separate the equalized signal into the
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%respective levels based on the actually
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%transmitted level!
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received(lvl,Tx_symbols.signal==constellation(lvl)) = Eq_signal.signal(Tx_symbols.signal==constellation(lvl));
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intermediate = received(lvl,:);
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cnt(lvl) = numel(intermediate(~isnan(intermediate)));
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hold on
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histogram(received(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' | ',num2str(cnt(lvl)),' entries']);
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end
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legend
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fprintf('BER: %.2e \n',ber);
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autoArrangeFigures;
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if ~isempty(curFolder)
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cd(curFolder);
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end
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end |