+++ Changes +++
+ duobinary_target now supports memoryless decoding (FFE targets DB response without MLSE) + PAMmapper.quantize now supports custom constellations for quantization + Added a new folder 'Documentations' for pdfs, slides, etc. + Added new FSO evaluation scripts in projects/FSO transmission/Evaluation Scripts + Added ffe_db (rudimentary module, not important anymore)
This commit is contained in:
magf
@@ -1,4 +1,4 @@
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close all;
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if 1
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@@ -8,8 +8,11 @@ if 1
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% uloops.laser_wavelength = [1293,1297.5,1302,1306.5,1310,1313.4,1318,1322.7,1327.4];
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uloops.laser_wavelength = [1293];
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uloops.M = [4];
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uloops.link_length = [0:2:10]; % 1,2,3,5,6,8,10
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uloops.link_length = 1;
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% uloops.link_length = [0:2:10]; % 1,2,3,5,6,8,10
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uloops.alpha = [0];
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uloops.duob_mode = db_mode.db_precoded;
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uloops.decoding_mode = "memoryless";
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wh = DataStorage(uloops);
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wh.addStorage("ber");
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@@ -22,8 +25,9 @@ end
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figure
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hold on
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for alpha = uloops.alpha
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a=wh.getStoValue('ber',1, [300].*1e9 , 1293, 4, uloops.link_length,alpha);
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ffe = cellfun(@(x) x.ffe_results.metrics.BER, a);
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a=wh.getStoValue('ber',1, [300].*1e9 , 1293, 4, uloops.link_length,alpha,uloops.duob_mode,uloops.decoding_mode);
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% ffe = cellfun(@(x) x.ffe_results.metrics.BER, a);
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ffe = cellfun(@(x) x.dbt_results.metrics.BER, a);
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plot(uloops.link_length,ffe,'DisplayName',sprintf('Alpha: %d',alpha),'LineStyle','-','HandleVisibility','on');
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end
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@@ -62,7 +62,7 @@ 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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% 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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@@ -132,7 +132,7 @@ 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.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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@@ -165,7 +165,7 @@ 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",1);
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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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@@ -174,54 +174,54 @@ Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
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%%% EQUALIZING
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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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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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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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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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output.dfe_results.metrics.print("description",'DFE');
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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 = [50, 5, 5];
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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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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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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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% % -------------------- 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, 5, 5];
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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", []);
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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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