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- Class folder 'Timing Recovery' with different timing recoveries
- Minimal example for the timing recovery on the FSO data
- New evaluation scripts in the FSO project folder
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magf
2026-02-02 10:56:12 +01:00
parent 798a0ca3b3
commit 005e821131
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projects/FSO_transmission/Evaluation Scripts/first_analysis_time_shift.m Normal file
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function BER = first_analysis_time_shift(time_shift)
%%
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)
% 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",2*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);
data_tr_mf = Electricalsignal(data_tr_mf.Results, "fs", fsym);
% 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};
Rx_matched_original = Rx_synced_cell{1};
Rx_matched_original.signal = resample(Rx_matched_original.signal,1,2);
[~,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};
Time_Rec = 1;
if Time_Rec
% [Rx_Time_Rec, Timing_Error] = Timing_Recovery("modulation", 'PAM/PSK/QAM', "timing_error_detector",'Gardner (non-data-aided)','sps',2,'damping_factor',1,'normalized_loop_bandwidth',1e-4,'detector_gain',2.7).process(Rx_matched_1);
Rx_Time_Rec = Time_Shifter('value',time_shift).process(Rx_matched_1);
Rx_Time_Rec.signal = resample(Rx_Time_Rec.signal,1,2);
% figure(2222222)
% plot(Timing_Error)
sps = 1;
else
sps = 2;
end
if Time_Rec == 1 && M == 2
Rx_Time_Rec.fs = 14e9;
elseif Time_Rec == 1 && M == 4
Rx_Time_Rec.fs = 6e9;
end
Rx_Time_Rec.spectrum('normalizeTo0dB',1,"displayname",'Our signal','fignum',101111);
% Rx_matched_original.spectrum('normalizeTo0dB',1,"displayname",'Our signal','fignum',101111);
Rx_tr_mf.spectrum('normalizeTo0dB',1,"displayname",'Their signal','fignum',101111);
Rx_Time_Rec_plot = Rx_Time_Rec;
% Rx_matched_original_plot = Rx_matched_original;
Rx_tr_mf_plot = Rx_tr_mf;
Rx_Time_Rec_plot.normalize("mode","rms").plot("displayname",'Our signal','fignum',101311);
% Rx_matched_original_plot.normalize("mode","rms").plot("displayname",'Original signal','fignum',101311);
Rx_tr_mf_plot.normalize("mode","rms").plot("displayname",'Their signal','fignum',101311);
%% not working..
% 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",[500, 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",[100, 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',200,'dfe_order',0,'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
BER = mlse_results.metrics.BER;
%% -------------------- ML-based MLSE (L=2) --------------------
% ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ...
% "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",11,"sps",sps, ...
% "traceback_depth",256,"L",4,"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
end