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sioe
2024-11-04 09:00:51 +01:00
parent 6dca327d10
commit 9ed763d094
5 changed files with 80 additions and 85 deletions
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132
projects/400G_FTN_setups/imdd_mpi_dsp.m
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@@ -5,17 +5,17 @@ params = struct;
params.M = [4];
params.datarate = [448];
params.rop = [0];
params.sir = 40;%15:1:40;
params.sir = 45;
params.random_key_laser_phase = 10:20;
precomp_mode = 0; %0=do nothing ; 1= measure; 2=precomp active
postfilter = 0; % noise whiten. approach -> Postfilter + MLSE
postfilter = 1; % noise whiten. approach -> Postfilter + MLSE
db_precode = 1;
db_precode = 0;
db_encode = 0;
db_channelapproach = 1;
db_channelapproach = 0;
laser_linewidth = 50e5;
laser_linewidth = 5e5;
random_key_sequence = 15;
random_key_laser_phase = 66;
sir = 20;
@@ -61,14 +61,14 @@ for M = wh.parameter.M.values
% MAIN SIGNAL
%%%%% Symbol Generation MAIN %%%%%%
[Digi_sig,Symbols,Bits] = PAMsource("fsym",fsym,"M",M,"order",18,"useprbs",1,...
[Digi_sig,Symbols,Bits] = PAMsource("fsym",fsym,"M",M,"order",19,"useprbs",1,...
"fs_out",M8199.fdac,"applyclipping",0,"clipfactor",1.5,...
"applypulseform",0,"pulseformer",Pform,"randkey",random_key_sequence,...
"db_precode",db_precode,"db_encode",db_encode,...
"mrds_code",usemrds,"mrds_blocklength",512).process();
%%%%% Symbol Generation INTERFERENCE %%%%%%
[Digi_sig_I,Symbols_I,Bits_I] = PAMsource("fsym",fsym,"M",M,"order",18,"useprbs",0,...
[Digi_sig_I,Symbols_I,Bits_I] = PAMsource("fsym",fsym,"M",M,"order",19,"useprbs",0,...
"fs_out",M8199.fdac,"applyclipping",0,"clipfactor",1.5,...
"applypulseform",0,"pulseformer",Pform,"randkey",random_key_sequence+1,...
"db_precode",db_precode,"db_encode",db_encode,...
@@ -185,8 +185,8 @@ for M = wh.parameter.M.values
end
% Scpe_sig_normalized = Scpe_sig.normalize("mode","rms");
% Scpe_sig.normalize("mode","rms").spectrum("displayname",'After Scope','fignum',10);
%
% Scpe_sig_normalized.normalize("mode","rms").spectrum("displayname",'After Scope','fignum',23);
%%%%%% Sample to 2x fsym %%%%%%
Scpe_sig = Scpe_sig.resample("fs_in",fadc,"fs_out",2*fsym);
@@ -213,11 +213,17 @@ for M = wh.parameter.M.values
if db_channelapproach
% ref symbols and transm. sequence are precoded
[EQ_sig, Noi] = Eq.process(Scpe_sig,Duobinary().encode(Symbols));
EQ_sig = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_sig);
EQ_sig = Duobinary().decode(EQ_sig);
Rx_bits = PAMmapper(M,0).demap(EQ_sig);
[~,~,ber_vnle(i,j),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
EQ_sig.spectrum('displayname','EQ DB Out','fignum',12345,'normalizeTo0dB',0,'normalizeToNyquist',0,'color',cols(3,:));
Noi.spectrum('displayname','Noise PSD optimal','fignum',1234,'normalizeTo0dB',0,'normalizeToNyquist',0,'color',cols(4,:));
elseif db_encode
[EQ_sig, Noi] = Eq.process(Scpe_sig,Symbols);
@@ -227,21 +233,39 @@ for M = wh.parameter.M.values
elseif postfilter
[EQ_sig, Noi] = Eq.process(Scpe_sig,Symbols);
% EQ_sig.plot("displayname",'After VNLE','fignum',90,'clear',1);
% Quantization is too far from orig. symbols ->
% error psd is quite different
% Sym_ = PAMmapper(M,0).quantize(EQ_sig);
% Noi_ = Sym_-EQ_sig;
% Noi_.normalize('mode','rms').spectrum('displayname','Noise PSD','fignum',1234,'normalizeTo0dB',1,'normalizeToNyquist',1,'color',cols(nc+1,:));
%%% REMOVE DC peak from Noi PSD
S = Noi.signal;
N1 = 1001;
% recursion
% Initialize the moving sum for the first window
half_window = (N1 - 1) / 2;
moving_sum = sum(S(1:N1));
% Calculate the first element of R1
S_(1:half_window+1) = S(1:half_window+1) - (moving_sum / N1);
% Loop over the signal and apply the recursive moving average subtraction
for n = (half_window+2):(length(S)-half_window)
% Update the moving sum by subtracting the oldest value and adding the new one
moving_sum = moving_sum - S(n-half_window-1) + S(n+half_window);
% Calculate the new value of R1
S_(n) = S(n) - (moving_sum / N1);
end
S_(n+1:length(S)) = S(n+1:end) - (moving_sum / N1);
Noi.signal = S_;
%%% END REMOVE DC PEAK %%%
Rx_bits = PAMmapper(M,0).demap(EQ_sig);
[~,~,ber_vnle(i,j),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
EQ_sig.normalize('mode','rms').spectrum('displayname','EQ Out','fignum',1234,'normalizeTo0dB',1,'normalizeToNyquist',1,'color',cols(nc,:));
Noi.normalize('mode','rms').spectrum('displayname','Noise PSD optimal','fignum',1234,'normalizeTo0dB',1,'normalizeToNyquist',1,'color',cols(nc+1,:));
EQ_sig.spectrum('displayname','EQ Out','fignum',12345,'normalizeTo0dB',0,'normalizeToNyquist',0,'color',cols(1,:));
Noi.spectrum('displayname','Noise PSD optimal','fignum',22,'normalizeTo0dB',1,'normalizeToNyquist',0,'color',cols(2,:));
for nc = 1:3
@@ -258,24 +282,16 @@ for M = wh.parameter.M.values
if 1
cols = linspecer(12);
% EQ_sig_filt.normalize('mode','rms').spectrum('displayname','Noise PSD','fignum',1234,'normalizeTo0dB',1,'normalizeToNyquist',0,'color',cols(nc+2,:));
EQ_sig_filt.normalize('mode','rms').spectrum('displayname','Noise PSD','fignum',1234,'normalizeTo0dB',1,'normalizeToNyquist',1,'color',cols(nc+2,:));
% [h,w] = freqz(1,burg_coeff,length(Noi),"whole",Noi.fs);
% h = h/max(abs(h));
% hold on
% w_ = (w - Noi.fs/2);
% figure(123)
% plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
[h,w] = freqz(1,burg_coeff,length(Noi),"whole");
[h,w] = freqz(1,burg_coeff,length(Noi),"whole",Noi.fs);
% h = 1./h;
h = h/max(abs(h));
hold on
w_ = (w - pi);
plot(w_,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
w_ = (w - Noi.fs/2);
figure(22)
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
end
Rx_bits = PAMmapper(M,0).demap(EQ_sig_mlse);
@@ -286,41 +302,7 @@ for M = wh.parameter.M.values
else
% S = Scpe_sig.signal;
% N1 = 101;
%
% % Initialize the running sum with the first window's sum
% running_sum = mean( S(1:N1) );
%
% % Calculate the first output value
% S_(1) = S(1) - running_sum;
%
% % Recursive running sum filter
% for n = 2 : length(S) - N1
% % Update running sum by removing the oldest sample and adding the newest
% avg_win(n) = mean( S(n:n+N1) );
% S_(n) = S(n) - avg_win(n);
% end
%
% % movmean
% S__ = S - movmean(S,[floor(N1/2),ceil(N1/2)]);
%
% % recursion
% % Initialize the moving sum for the first window
% half_window = (N1 - 1) / 2;
% moving_sum = sum(S(1:N1));
%
% % Calculate the first element of R1
% S___(half_window+1) = S(half_window+1) - (moving_sum / N1);
%
% % Loop over the signal and apply the recursive moving average subtraction
% for n = (half_window+2):(length(S)-half_window)
% % Update the moving sum by subtracting the oldest value and adding the new one
% moving_sum = moving_sum - S(n-half_window-1) + S(n+half_window);
%
% % Calculate the new value of R1
% S___(n) = S(n) - (moving_sum / N1);
% end
[EQ_sig, Noi] = Eq.process(Scpe_sig,Symbols);
@@ -379,16 +361,16 @@ ber_mlse=squeeze(mean(ber_mlse,1));
ber_vnle = mean(ber_vnle,1);
% Create the initial plot
figure(44);
figure(466);
a = gca;
hold on; % Retain the plot so new points can be added without complete redraw
dispname = ['Lw: ',num2str(laser_linewidth.*1e-6),' MHz'];
plot(wh.parameter.sir.values,ber_vnle,"LineWidth",0.5,"LineStyle","-","Marker",".","MarkerSize",15,"DisplayName",['VNLE ',dispname]);
plot(wh.parameter.sir.values,ber_mlse(:,1),"LineWidth",0.5,"LineStyle","-","Marker",".","MarkerSize",15,"DisplayName",['MLSE 1 ',dispname]);
plot(wh.parameter.sir.values,ber_mlse(:,2),"LineWidth",0.5,"LineStyle","-","Marker",".","MarkerSize",15,"DisplayName",['MLSE 2',dispname]);
plot(wh.parameter.sir.values,ber_mlse(:,3),"LineWidth",0.5,"LineStyle","-","Marker",".","MarkerSize",15,"DisplayName",['MLSE 3',dispname]);
cols = linspecer(6);
plot(wh.parameter.sir.values,ber_vnle,"LineWidth",0.5,"LineStyle","--","Marker",".","MarkerSize",15,"DisplayName",['PAM',num2str(M),' VNLE ',dispname],'Color',cols(1,:));
plot(wh.parameter.sir.values,ber_mlse(:,1),"LineWidth",0.5,"LineStyle","--","Marker",".","MarkerSize",15,"DisplayName",['PAM',num2str(M),'MLSE 1 ',dispname],'Color',cols(2,:));
plot(wh.parameter.sir.values,ber_mlse(:,2),"LineWidth",0.5,"LineStyle","--","Marker",".","MarkerSize",15,"DisplayName",['PAM',num2str(M),'MLSE 2',dispname],'Color',cols(3,:));
plot(wh.parameter.sir.values,ber_mlse(:,3),"LineWidth",0.5,"LineStyle","--","Marker",".","MarkerSize",15,"DisplayName",['PAM',num2str(M),'MLSE 3',dispname],'Color',cols(4,:));
yline(3.8e-3,'DisplayName','HD-FEC','LineStyle','--','HandleVisibility','off');
xlabel('Received Optical Power (dBm)');

5
projects/Lab_2024/offline_dsp_analysis/load_n_dsp.m
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@@ -1,13 +1,14 @@
% load data points
if 0
foldername = '/Users/silasoettinghaus/Nextcloud/Dokumente/02_Ablage_Office/Lab_Data_24/sir_sweep_sd40/';
foldername = 'C:\Users\Silas\Nextcloud4\Dokumente\02_Ablage_Office\Lab_Data_24\sir_sweep_sd40';
filename = 'PAM4_56_';
filename = 'PAM4_56_v2';
else
foldername = '/Users/silasoettinghaus/Nextcloud/Dokumente/02_Ablage_Office/Lab_Data_24/sir_sweep_sd40/DB_coded';
foldername = 'C:\Users\Silas\Nextcloud4\Dokumente\02_Ablage_Office\Lab_Data_24\sir_sweep_sd40\DB_coded';
filename = 'PAM4_68_v2';
end
stuff = load([foldername,filesep,filename,'wh']);
%stuff = load([foldername,filesep,'PAM4_v2_10km_wh']);
wh = stuff.obj;

8
projects/Lab_2024/offline_dsp_analysis/load_n_plot_transfer_characteristic.m Normal file
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@@ -0,0 +1,8 @@
precomp_path = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\standard_system";
precomp_filename = "lab_mpi_setup_2";
freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
freqresp.load('loadPath',precomp_path,'fileName',precomp_filename);
freqresp.plot();