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new minimal example

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new project: FSO stuff
This commit is contained in:
silas (home)
2026-01-07 15:07:38 +01:00
parent cfc142b676
commit 5c39a7f98a
8 changed files with 185 additions and 25 deletions
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3
Classes/00_signals/Electricalsignal.m
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@@ -108,9 +108,6 @@ classdef Electricalsignal < Signal
obj.signal = obj.signal*scling;
end
end
end

1
Classes/00_signals/Opticalsignal.m
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@@ -71,7 +71,6 @@ classdef Opticalsignal < Signal
cspr = 10*log10(c / s);
end

18
Classes/00_signals/Signal.m
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@@ -98,7 +98,6 @@ classdef Signal
end
%% CONVERT TO Opticalsignal
function o_sig = Opticalsignal(obj, options)
@@ -273,7 +272,6 @@ classdef Signal
SignalCopy = [];
ModifierName = class(CallingModifier);
cell = {SignalType , TimeStamp , Length , SignalPower(1) , Nase, SignalCopy, ModifierName, ModifierCopy, Description};
obj.logbook = [obj.logbook; cell];
@@ -364,7 +362,6 @@ classdef Signal
end
if options.normalizeToNyquist == 0
[p_lin,f_Hz] = pwelch(obj.signal, hanning(options.fft_length), ...
options.fft_length/2, options.fft_length, ...
@@ -488,7 +485,6 @@ classdef Signal
end
function move_it_spectrum(obj,options)
arguments
obj
@@ -630,7 +626,6 @@ classdef Signal
case power_notation.W
%pow = pow % Watt
end
end
@@ -668,7 +663,7 @@ classdef Signal
%% PAPR of signal
function papr_db = papr_db(obj)
%PAPR The peak-to-average power ratio (PAPR) is the peak amplitude squared (giving the peak power)
% PAPR The peak-to-average power ratio (PAPR) is the peak amplitude squared (giving the peak power)
% divided by the RMS value squared (giving the average power).[1] It is the square of the crest factor.
% papr = max(abs(timesignal))^2 / rms(timesignal)^2; ODER papr = peak2rms(sig)^2;
@@ -732,14 +727,11 @@ classdef Signal
options.debug_plots = 0;
end
S = {};
inverted = -1;
sequenceFound = 0;
sequenceStarts = [];
%normalize the signal
a = obj.normalize("mode","oneone").signal;
@@ -777,8 +769,6 @@ classdef Signal
findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend')
end
shifts = lags(pkpos);
sequenceStarts = shifts;
shifts = shifts(shifts>=0);
@@ -831,7 +821,6 @@ classdef Signal
end
%%
function obj = filter(obj,a,b)
@@ -921,6 +910,7 @@ classdef Signal
end
%%
function eye(obj,fsym,M,options)
@@ -981,8 +971,8 @@ classdef Signal
maxA = max(sig(100:end-100))*1.3;
minA = min(sig(100:end-100))*1.3;
maxA = 0.12;
minA = -0.08;
% maxA = 0.12;
% minA = -0.08;
difference= maxA-minA;

1
Functions/Metrics/air_garcia_implementation.m
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@@ -11,7 +11,6 @@ if nargin == 4
M_training = [];
end
% if input is complex, separate into real and imaginary parts
if any(imag(x(:))~=0) || any(imag(r(:))~=0)
x = [real(x); imag(x)];

12
projects/FSO_transmission/first_analysis.m Normal file
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@@ -0,0 +1,12 @@
datas = load("C:\Users\Silas\Downloads\FSO_FP_QCL_60umUTC\FSO_FP_QCL_60umUTC\6G_PAM4\M=4_Rs=6e9_Fs=8e10_I=225mA_RoP=28.02mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
fsym = 6e9;
fs = 80e9;
rawsignal = datas.tr.lastData(1).trace.ch3.RawData;
Scope_sig = Electricalsignal(rawsignal,"fs",fs);
Scope_sig.plot("displayname",'raw','fignum',100);

7
projects/IMDD_base_system/imdd_it.m
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@@ -1,6 +1,7 @@
if 1
uloops = struct;
uloops.precomp = [1];
uloops.bitrate = [300].*1e9; %[300,330,360,390,420,450,480] [224,336,360,390,420,448] for MPI
@@ -8,12 +9,12 @@ if 1
uloops.laser_wavelength = [1293];
uloops.M = [4];
uloops.link_length = [0:2:10]; % 1,2,3,5,6,8,10
uloops.alpha = [0.5,-0.5,0];
uloops.alpha = [0];
wh = DataStorage(uloops);
wh.addStorage("ber");
wh = submit_handle(@imdd_model,wh,"parallel",1);
wh = submit_handle(@imdd_model,wh,"parallel",0);
end
@@ -34,6 +35,8 @@ beautifyBERplot()
ylabel('BER');
%
% wh_ana = wh_master;
%

6
projects/IMDD_base_system/imdd_model.m
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@@ -92,9 +92,13 @@ if fsym_ ~= fsym
% 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);
end
f_nyquist = fsym/2;
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
[Digi_sig,Symbols,Tx_bits] = PAMsource(...
"fsym",fsym,"M",M,"order",18,"useprbs",0,...

156
projects/IMDD_base_system/minimal_example.m Normal file
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@@ -0,0 +1,156 @@
% minimal example IM/DD
M = 4;
fsym = 180e9;
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 = -8;
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","rc","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',100,'normalizeTo0dB',0);
% 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);
%%%%%% 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",0);
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);
% -------------------- 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
% -------------------- 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);
% -------------------- 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');