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Merge branch 'main' of cau-git.rz.uni-kiel.de:nt/mitarbeiter/silas/imdd_simulation

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Silas Oettinghaus
2026-03-12 17:27:23 +01:00
parent 4c78a1e0b1 3676d92b30
commit 0577ffe7f6
32 changed files with 2365 additions and 288 deletions
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101
projects/IMDD_base_system/imdd_model.m
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@@ -62,7 +62,7 @@ mu_dfe = 0.0004;
dfe_ = sum(dfe_order)>0;
duob_mode = db_mode.no_db;
% duob_mode = db_mode.no_db;
%%% change specific parameter if given in varargin
% Parse optional input arguments
@@ -77,7 +77,7 @@ if ~isempty(varargin)
else
eval([fields{i}, ' = ', 'var_s.(fields{',num2str(i),'})' , ';']);
end
end
else
error('Optional variables should be passed as a struct.');
@@ -132,7 +132,7 @@ 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.spectrum("displayname",'Opt Spectrum','fignum',10,'normalizeTo0dB',1);
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);
@@ -165,7 +165,7 @@ 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,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
@@ -180,57 +180,60 @@ if 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);
output.ffe_results = ffe(eq_ffe,M,Scpe_sig,Symbols,Tx_bits, ...
"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
"eth_style_symbol_mapping",0);
output.ffe_results.metrics.print
end
if 0
% -------------------- DFE --------------------
eq_dfe = 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);
output.dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits, ...
"precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
"eth_style_symbol_mapping",0);
output.dfe_results.metrics.print("description",'DFE');
end
if 0
% -------------------- 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', 0, "postFFE", [], "eth_style_symbol_mapping", 0);
end
if 1
% % -------------------- FFE --------------------
% ffe_order = [50, 0, 0];
% eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0], ...
% "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);
%
% output.ffe_results = ffe(eq_ffe,M,Scpe_sig,Symbols,Tx_bits, ...
% "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
% "eth_style_symbol_mapping",0);
%
% output.ffe_results.metrics.print
% % -------------------- DFE --------------------
% eq_dfe = 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);
%
% output.dfe_results = ffe(eq_dfe,M,Scpe_sig,Symbols,Tx_bits, ...
% "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
% "eth_style_symbol_mapping",0);
%
% output.dfe_results.metrics.print("description",'DFE');
% % -------------------- VNLE + MLSE --------------------
% pf_ncoeffs = 1;
% ffe_order3 = [200, 0, 0];
% 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', 0, "postFFE", [], "eth_style_symbol_mapping", 0);
% -------------------- DB target --------------------
mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
ffe_order = [50, 5, 5];
ffe_order = [50, 0, 0];
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", []);
"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", [], "decoding_mode", decoding_mode);
output.dbt_results.metrics.print("description",'Duobinary');
disp('- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ')
fprintf('\n')
end
end