Add partial response symbol mapping and IM/DD system example
- Implemented a new MATLAB script for partial response symbol mapping using Duobinary precoding. - Added functions for printing constellation bit mapping and partial response state tables. - Created a minimal example for an IM/DD system, including signal generation, modulation, and equalization processes. - Integrated various components such as pulse shaping, optical modulation, and receiver processing. - Included detailed configurations for parameters like bias, link length, and filter settings.
This commit is contained in:
Silas Oettinghaus
182
projects/Precoding_analysis/precode_imdd_system.m
Normal file
182
projects/Precoding_analysis/precode_imdd_system.m
Normal file
@@ -0,0 +1,182 @@
|
||||
% minimal example IM/DD
|
||||
|
||||
M = 4;
|
||||
fsym = 112e9;
|
||||
|
||||
apply_pulsef = 1;
|
||||
fdac = 256e9;
|
||||
fadc = 256e9;
|
||||
random_key = 1;
|
||||
|
||||
rcalpha = 0.05;
|
||||
kover = 16;
|
||||
|
||||
duob_mode = db_mode.no_db;
|
||||
|
||||
vbias_rel = 0.5;
|
||||
u_pi = 3;
|
||||
vbias = -vbias_rel*u_pi;
|
||||
|
||||
laser_wavelength = 1293;
|
||||
laser_linewidth = 0;
|
||||
tx_bw_nyquist = 0.8;
|
||||
|
||||
% Channel
|
||||
link_length = 1;
|
||||
|
||||
% RX
|
||||
rop = -9;
|
||||
rx_bw_nyquist = 0.8;
|
||||
|
||||
vnle_order1 = 50;
|
||||
vnle_order2 = 7;
|
||||
vnle_order3 = 7;
|
||||
|
||||
vnle_order=[vnle_order1,vnle_order2,vnle_order3];
|
||||
dfe_order = [0 0 0];
|
||||
|
||||
pf_ncoeffs = 1;
|
||||
|
||||
alpha = 0;
|
||||
|
||||
len_tr = 4096*2;
|
||||
|
||||
mu_ffe1 = 0.0001;
|
||||
mu_ffe2 = 0.0008;
|
||||
mu_ffe3 = 0.001;
|
||||
mu_dc = 0.005;
|
||||
% mu_dc = 0;
|
||||
|
||||
mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
|
||||
mu_dfe = 0.0004;
|
||||
|
||||
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
|
||||
|
||||
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
|
||||
"fsym",fsym,"M",M,"order",18,"useprbs",0,...
|
||||
"fs_out",fdac,...
|
||||
"applyclipping",0,"clipfactor",1.5,...
|
||||
"applypulseform",apply_pulsef,"pulseformer",Pform,...
|
||||
"randkey",random_key,...
|
||||
'duobinary_mode',duob_mode,...
|
||||
"mrds_code",0,"mrds_blocklength",512).process();
|
||||
|
||||
%%%%% AWG
|
||||
% El_sig = M8199A("kover",kover).process(Digi_sig);
|
||||
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);
|
||||
El_sig.spectrum("displayname",'Digi Spectrum','fignum',1,'normalizeTo0dB',1);
|
||||
xlim([0,130]);
|
||||
ylim([-30,5]);
|
||||
% El_sig = El_sig.setPower(0,"dBm");
|
||||
|
||||
%%%%% Electrical Driver Amplifier %%%%%%
|
||||
% El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
|
||||
El_sig = El_sig.normalize("mode","oneone");
|
||||
scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2));
|
||||
El_sig = El_sig .* scaling;
|
||||
|
||||
%%%%% MODULATE E/O CONVERSION %%%%%%
|
||||
[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);
|
||||
|
||||
Opt_sig.spectrum("displayname",'Opt Spectrum','fignum',10,'normalizeTo0dB',1);
|
||||
|
||||
% Opt_sig.eye(fsym,M,"displayname",'eye adter modulator','fignum',2026);
|
||||
|
||||
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);
|
||||
|
||||
%%%%%% ROP %%%%%%
|
||||
Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",rop).process(Opt_sig);
|
||||
|
||||
%%%%%% PD Square Law %%%%%%
|
||||
Rx_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11).process(Rx_sig);
|
||||
|
||||
%%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%%
|
||||
rx_bwl = 80e9;
|
||||
Rx_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(Rx_sig);
|
||||
|
||||
% %%%%%% Low-pass Scope %%%%%%
|
||||
Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true);
|
||||
|
||||
%%%%%% Scope %%%%%%
|
||||
Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
|
||||
"delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,...
|
||||
"samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,...
|
||||
"adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(Rx_sig);
|
||||
%%
|
||||
|
||||
% 1) matched filter
|
||||
% pulse is symmetric, hence we can use pulsef firectly as matched filter.
|
||||
% It feels off (bit I think correct) that the fsym is now the output freq.!!
|
||||
% -> output 2 sps to omit timing recovery!?
|
||||
Pform = Pulseformer("fsym",fsym,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha,"matched",1);
|
||||
Scpe_sig = Pform.process(Scpe_sig);
|
||||
Scpe_sig.spectrum("displayname",'Signal after matched filter','fignum',1,'normalizeTo0dB',1);
|
||||
%
|
||||
|
||||
% %%
|
||||
% %%%%%% Sample to 2x fsym %%%%%%
|
||||
% Scpe_sig = Scpe_sig.resample("fs_out",2*fsym);
|
||||
% Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
|
||||
|
||||
%%
|
||||
%%%%%% Sync Rx signal with reference %%%%%%
|
||||
[Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",1);
|
||||
Scpe_sig.spectrum("displayname",'Opt Spectrum','fignum',11,'normalizeTo0dB',1);
|
||||
|
||||
% Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
|
||||
|
||||
Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
|
||||
Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
|
||||
|
||||
%%
|
||||
|
||||
% -------------------- FFE --------------------
|
||||
ffe_order = [50, 0, 0];
|
||||
eq_ = 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);
|
||||
|
||||
% eq_ = FFE("epochs_tr",4,"epochs_dd",5,"len_tr",4096,"mu_dd",0.01,"mu_tr",0.01,"order",50,"sps",2,"decide",0, "adaption",adaption_method.nlms,"dd_mode",1);
|
||||
eq_ = FFE_DFE("epochs_tr",5,"epochs_dd",5,"len_tr",512,"ffe_mu_dd",1e-4,"dfe_mu_dd",5e-4,"ffe_mu_tr",0,"dfe_mu_tr",0,"ffe_order",99,"dfe_order",99,"sps",2,"decide",0);
|
||||
|
||||
|
||||
output.ffe_results = ffe(eq_,M,Scpe_sig,Symbols,Tx_bits, ...
|
||||
"precode_mode",duob_mode,'showAnalysis',1,"postFFE",[], ...
|
||||
"eth_style_symbol_mapping",0);
|
||||
|
||||
output.ffe_results.metrics.print("description",'DFE');
|
||||
|
||||
%%
|
||||
|
||||
% -------------------- VNLE + MLSE --------------------
|
||||
pf_ncoeffs = 1;
|
||||
ffe_order3 = [50, 5, 5];
|
||||
eq_v = EQ("Ne",ffe_order3,"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);
|
||||
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
|
||||
|
||||
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
|
||||
|
||||
[output.vnle_results, output.mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
|
||||
"precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", 0);
|
||||
|
||||
output.mlse_results.metrics.print("description",'MLSE');
|
||||
|
||||
%%
|
||||
|
||||
% -------------------- DB target --------------------
|
||||
mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
|
||||
ffe_order = [50, 5, 5];
|
||||
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);
|
||||
output.dbt_results = duobinary_target(eq_,mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
|
||||
"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", []);
|
||||
|
||||
output.dbt_results.metrics.print("description",'Duobinary');
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user