251 lines
11 KiB
Matlab
251 lines
11 KiB
Matlab
%%
|
||
clear all;
|
||
close all;
|
||
|
||
%% Choose a fitting base leading to the FSO Data
|
||
base = "C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\FSO_FP_QCL_60umUTC\";
|
||
mode = 0; %0 oder 1
|
||
M = 4;
|
||
|
||
all_files = dir(fullfile(base, "**/*.mat"));
|
||
|
||
% data_tr_mf is the already recovered and filtered data
|
||
if M == 2
|
||
tx_data_path = fullfile(base, "14G_PAM2\tx_info\tx_info_PAM2_14Gbd0.75RRC.mat");
|
||
filename = fullfile(base, "14G_PAM2\M=2_Rs=1.4e10_Fs=8e10_I=265mA_RoP=46.3mW_L=31m_PS=RRC_rolloff=0.75_Mode=Rise.mat");
|
||
data_tr_mf = load("C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\FSO_FP_QCL_60umUTC\Already Recovered and Filtered\AfterSync_M=2_Rs=1.4e10_Fs=8e10_I=265mA_RoP=46.3mW_L=31m_PS=RRC_rolloff=0.75_Mode=Rise.mat");
|
||
elseif M == 4
|
||
tx_data_path = fullfile(base, "6G_PAM4\tx_info\tx_info_PAM4_6Gbd0.6RRC.mat");
|
||
filename = fullfile(base, "6G_PAM4\M=4_Rs=6e9_Fs=8e10_I=255mA_RoP=42.3mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
|
||
data_tr_mf = load("C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\FSO_FP_QCL_60umUTC\Already Recovered and Filtered\AfterSync_M=4_Rs=6e9_Fs=8e10_I=255mA_RoP=42.3mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat");
|
||
end
|
||
|
||
if mode == 1
|
||
[f, p] = uigetfile(fullfile(base, "**/*.mat"));
|
||
if f~=0
|
||
filename = fullfile(p,f);
|
||
end
|
||
end
|
||
|
||
tx_data = load(tx_data_path);
|
||
datas = load(filename);
|
||
|
||
%%
|
||
str = filename;
|
||
M_ = str2double(regexp(str, 'M=([^_]+)', 'tokens', 'once'));
|
||
assert(M==M_);
|
||
fsym = str2double(regexp(str, 'Rs=([^_]+)', 'tokens', 'once'));
|
||
fs = str2double(regexp(str, 'Fs=([^_]+)', 'tokens', 'once'));
|
||
I = sscanf(char(regexp(str, 'I=([^_]+)', 'tokens', 'once')), '%f');
|
||
rop = sscanf(char(regexp(str, 'RoP=([^_]+)', 'tokens', 'once')), '%f');
|
||
L = sscanf(char(regexp(str, 'L=([^_]+)', 'tokens', 'once')), '%f');
|
||
pulseshape = string( regexp(str, 'PS=([^_]+)', 'tokens', 'once'));
|
||
rolloff = str2double(regexp(str, 'rolloff=([^_]+)', 'tokens', 'once'));
|
||
mode = string( regexp(str, 'Mode=([^\.]+)', 'tokens', 'once'));
|
||
|
||
%%
|
||
% Tx data
|
||
|
||
Bits = Informationsignal(tx_data.tx_data,"fs",fsym);
|
||
Symbols = Informationsignal(real(tx_data.tx_PAM_sym),"fs",fsym);
|
||
|
||
mapping_style = M==4; % Pam2 is like move-it; PAM-4 is different, same mapping like ETH peopled used in Zurich... hence the "eth_style" argument here and there
|
||
PM = PAMmapper(M,0,"eth_style",mapping_style); % one should rename "eth style" as this is simply a different mapping scheme
|
||
|
||
Symbols_ = PM.map(Bits) .* PM.scaling;
|
||
assert(isequal(Symbols.signal,Symbols_.signal));
|
||
|
||
Bits_ = PM.demap(Symbols);
|
||
[bits,errors,ber,errorIndice] = calc_ber(Bits_.signal,Bits.signal);
|
||
assert(ber == 0);
|
||
|
||
%% For comparison, apply pulsef on Tx Symbols
|
||
Pform = Pulseformer("fsym",fsym,"fdac",fs,"pulse","rrc","pulselength",16,"alpha",rolloff);
|
||
Digi_sig_compare = Pform.process(Symbols);
|
||
|
||
MF = Pulseformer("fsym",fsym,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rolloff);
|
||
Rx_sig_compare = MF.process(Digi_sig_compare);
|
||
|
||
%%
|
||
|
||
% Rx Data
|
||
traceData = datas.tr.lastData(2).trace.ch3;
|
||
|
||
%FYI: Voltage=(RawData−YReference)×YIncrement+YOrigin
|
||
scoperead_volts = (traceData.RawData - traceData.YReference) * traceData.YIncrement + traceData.YOrigin;
|
||
demystified = isequal(traceData.YData,scoperead_volts);
|
||
assert(demystified);
|
||
|
||
Scope_sig = Electricalsignal(traceData.YData,"fs",fs);
|
||
|
||
Scope_sig.plot("displayname",'raw','fignum',100);
|
||
Scope_sig.spectrum("displayname",'raw','fignum',101)
|
||
|
||
%Calculate Transfer Function
|
||
Tx_spectrum = Digi_sig_compare;
|
||
Rx_spectrum = Scope_sig;
|
||
|
||
[~,Rx_synced_spectrum,inverted_spectrum,sequenceFound_spectrum,sequenceStarts_spectrum] = Rx_spectrum.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
|
||
Rx_spectrum = Rx_synced_spectrum{1};
|
||
|
||
Tx_spectrum = Tx_spectrum.resample("fs_out",fsym);
|
||
Tx_spectrum.signal = fft(Tx_spectrum.signal);
|
||
|
||
Rx_spectrum = Rx_spectrum.resample("fs_out",fsym);
|
||
Rx_spectrum.signal = fft(Rx_spectrum.signal);
|
||
|
||
H_transfer = Rx_spectrum.signal./Tx_spectrum.signal;
|
||
H_inv = 1./H_transfer;
|
||
|
||
%Number of Samples/Symbol after Matched Filter
|
||
Kov = 14;
|
||
|
||
Scope_sig = Scope_sig.resample('fs_in',fs,'fs_out',Kov*fsym);
|
||
|
||
% 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!?
|
||
Matched_Filter = Pulseformer("fsym",fsym,"fdac",Kov*fsym,"pulse","rrc","pulselength",16,"alpha",rolloff,"matched",1);
|
||
Rx_matched = Matched_Filter.process(Scope_sig);
|
||
Rx_matched.spectrum("displayname",'Signal after matched filter','fignum',1);
|
||
|
||
% Loading and synchronizing their matched filtered and timing recovered data
|
||
data_tr_mf = Electricalsignal(data_tr_mf.Results, "fs", fsym);
|
||
[~,Rx_synced_cell_tr_mf,inverted_tr_mf,sequenceFound_tr_mf,sequenceStarts_tr_mf] = data_tr_mf.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
|
||
Rx_tr_mf = Rx_synced_cell_tr_mf{1};
|
||
|
||
% Timing sync -> at this point we still have no symbol timing recovery, we
|
||
% try to do this with 2sps EQ!
|
||
[~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1);
|
||
Rx_matched_1 = Rx_synced_cell{1};
|
||
|
||
% Timing recovery
|
||
Time_Rec = 1;
|
||
Timing_Mode = 3;
|
||
if Time_Rec
|
||
if Timing_Mode == 1 % Zero-Crossing/Gardner/Early-Late/Müller-Mueller Timing Recovery
|
||
[Rx_Time_Rec, Timing_Error] = Timing_Recovery("modulation", 'PAM/PSK/QAM', "timing_error_detector",'Gardner (non-data-aided)','sps',Kov,'damping_factor',1,'normalized_loop_bandwidth',1e-4,'detector_gain',2.7).process(Rx_matched_1);
|
||
elseif Timing_Mode == 2 % Godard Timing Recovery (resampling is required as the Godard timing recovery does not change the number of samples per symbol)
|
||
[Rx_Time_Rec, Timing_Error_MG] = Godard_Timing_Recovery('mode',3,'num_blocks',1,'fft_length',length(Rx_matched_1),'sps',Kov,'rolloff',0.6,'mu',-0.2,'Ki',1e-4).process(Rx_matched_1);
|
||
Rx_Time_Rec = Rx_Time_Rec.resample('fs_in',Kov*fsym,'fs_out',fsym);
|
||
elseif Timing_Mode == 3 % Maximum Variance Timing Recovery
|
||
Rx_Time_Rec = MaxVar_Timing_Recovery('mode',0,'fsym',fsym,'fadc',Kov*fsym,'num_tau',Kov*128,'sps',Kov,'comp_signal',Rx_tr_mf,'comp_mode',0).process(Rx_matched_1);
|
||
end
|
||
else
|
||
Rx_Time_Rec = Rx_matched_1.resample('fs_in',Kov*fsym,'fs_out',fsym);
|
||
end
|
||
sps = 1;
|
||
Rx_Time_Rec.fs = fsym;
|
||
|
||
% % Compensate using the inverse transfer function
|
||
% Amax = 10;
|
||
% H_inv = min(abs(H_inv), Amax) .* exp(1j*angle(H_inv));
|
||
% Rx_Time_Rec.signal = fft(Rx_Time_Rec.signal);
|
||
% Rx_Time_Rec.signal = ifft(Rx_Time_Rec.signal .* H_inv);
|
||
|
||
% Normalization
|
||
Rx_Time_Rec = Rx_Time_Rec.normalize('mode','rms');
|
||
Rx_tr_mf = Rx_tr_mf.normalize('mode','rms');
|
||
|
||
% Compare spectra of our and their time signal
|
||
Rx_Time_Rec.spectrum("displayname",'Our signal','normalizeTo0dB',1,'fignum',101111);
|
||
% Rx_matched_original.spectrum('normalizeTo0dB',1,"displayname",'Our signal','fignum',101111);
|
||
Rx_tr_mf.spectrum("displayname",'Their signal','normalizeTo0dB',1,'fignum',101111);
|
||
|
||
% Compare our and their time signal
|
||
Rx_Time_Rec.normalize("mode","rms").plot("displayname",'Our signal','fignum',101311);
|
||
% Rx_matched_original.normalize("mode","rms").plot("displayname",'Original signal','fignum',101311);
|
||
Rx_tr_mf.normalize("mode","rms").plot("displayname",'Their signal','fignum',101311);
|
||
|
||
%%
|
||
% Use our or their signal
|
||
for our_signal = 1
|
||
if our_signal
|
||
Rx_synced = Rx_Time_Rec;
|
||
else
|
||
Rx_synced = Rx_tr_mf;
|
||
end
|
||
% Rx_synced = Rx_Time_Rec;
|
||
% Rx_synced = Rx_synced_cell{1};
|
||
len_tr = 4096*2;
|
||
mu_ffe1 = 0.0001;
|
||
mu_ffe2 = 0.0008;
|
||
mu_ffe3 = 0.001;
|
||
mu_dc = 0.004;
|
||
mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
|
||
mu_dfe = 0.0004;
|
||
duob_mode = db_mode.no_db;
|
||
|
||
Rx_synced.plot("displayname",'RX: Matched+Sync+2sps','fignum',103);
|
||
Rx_synced.spectrum("displayname",'RX: Matched+Sync+2sps','fignum',104);
|
||
|
||
Digi_sig_compare.normalize("mode","rms").spectrum("displayname",'Tx: RC-shaped','fignum',1,'normalizeTo0dB',1);
|
||
Rx_sig_compare.normalize("mode","rms").spectrum("displayname",'Tx: RC-shaped + matched filtered ','fignum',1,'normalizeTo0dB',1);
|
||
Rx_synced.normalize("mode","rms").spectrum("displayname",'RX: matched filtered + synced','fignum',1,'normalizeTo0dB',1);
|
||
|
||
if M == 2
|
||
ber_in_paper = 10^(-2.6); %fig 3a) 4 Gb/s MWIR FSO Transmission using Directly Modulated QCL and an Uncooled UTC-PD at Room-Temperature
|
||
elseif M == 4
|
||
ber_in_paper = 10^(-2.5);
|
||
end
|
||
|
||
%% -------------------- FFE --------------------
|
||
% requires some more digging what is going on :-)
|
||
% eq_ffe = EQ("Ne",[150, 0, 0],"Nb",[0,0,0], ...
|
||
% "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
|
||
% "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
|
||
% "FFEmu",0,"plotfinal",0,"ideal_dfe",1);
|
||
%
|
||
% % eq_ffe = FFE_DFE('ffe_order',99,'dfe_order',99,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5,'sps',sps,'decide',0);
|
||
%
|
||
% ffe_results = ffe(eq_ffe,M,Rx_synced,Symbols,Bits, ...
|
||
% "precode_mode",duob_mode,'showAnalysis',0,"postFFE",[], ...
|
||
% "eth_style_symbol_mapping",mapping_style);
|
||
%
|
||
% if our_signal
|
||
% fprintf('Our signal: %.1e \n',ffe_results.metrics.BER);
|
||
% fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
% else
|
||
% fprintf('Their signal: %.1e \n',ffe_results.metrics.BER);
|
||
% fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
% end
|
||
|
||
%% -------------------- VNLE + MLSE --------------------
|
||
% pf_ncoeffs = 4;
|
||
% eq_v = EQ("Ne",[300, 0, 0],"Nb",[0, 0, 0], ...
|
||
% "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
|
||
% "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
|
||
% "FFEmu",0,"plotfinal",0,"ideal_dfe",1, ...
|
||
% 'weighted_DFE',0,'weighted_DFE_d_min',0.5,'weighted_DFE_mode','R2','weighted_DFE_I_mode',[5,0.5,0.6]);
|
||
% % eq_v = FFE_DFE('ffe_order',300,'dfe_order',5,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5, ...
|
||
% % 'ffe_mu_dd',mu_ffe,'ffe_mu_tr',0,'dfe_mu_dd',mu_dfe,'dfe_mu_tr',0.005,'sps',sps,'decide',0);
|
||
% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
|
||
% mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
|
||
%
|
||
% [vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Rx_synced, Symbols, Bits, ...
|
||
% "precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", mapping_style);
|
||
%
|
||
% mlse_results.metrics.print
|
||
% if our_signal
|
||
% fprintf('Our Signal: %.1e \n',mlse_results.metrics.BER);
|
||
% fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
% else
|
||
% fprintf('Their Signal: %.1e \n',mlse_results.metrics.BER);
|
||
% fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
% end
|
||
|
||
%% -------------------- ML-based MLSE (L=2) --------------------
|
||
ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ...
|
||
"len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",210,"sps",sps, ...
|
||
"traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0);
|
||
|
||
[ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);
|
||
if our_signal
|
||
fprintf('Our Signal: %.1e \n',ml_mlse_results.metrics.BER);
|
||
fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
else
|
||
fprintf('Their EQ: %.1e \n',ml_mlse_results.metrics.BER);
|
||
fprintf('Paper: %.1e \n \n',ber_in_paper);
|
||
end
|
||
end |