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FFE now has a automatic optimization of the mu-parameters -> enables the fast comparison of LMS, NLMS and RLS and also good for very long filters (1000+ taps) which might be unstable else.

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Minor changes here and there
This commit is contained in:
Silas Oettinghaus
2026-05-12 10:40:03 +02:00
parent 56b48095db
commit f883071dec
13 changed files with 524 additions and 65 deletions
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42
projects/IMDD_base_system/minimal_example.m
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@@ -1,7 +1,7 @@
% minimal example IM/DD
M = 4;
fsym = 112e9;
fsym = 180e9;
apply_pulsef = 1;
fdac = 256e9;
@@ -63,8 +63,8 @@ Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"al
"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 = M8199B("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]);
@@ -130,24 +130,24 @@ 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');
if 0
% -------------------- 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');
end
%%
% -------------------- VNLE + MLSE --------------------