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Last commit after 400G Lab Measurement

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This commit is contained in:
Silas Labor Zizou
2024-11-04 08:57:53 +01:00
parent cf4e0f2b12
commit 492f889dce
9 changed files with 669 additions and 266 deletions
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7
Classes/04_DSP/Coding/Duobinary.m
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@@ -125,6 +125,13 @@ classdef Duobinary
%make bipolar
data = (data-round(mean(data),1));
[unique_points, ~, idx] = unique(data);
counts = accumarray(idx, 1);
total_samples = numel(data);
probabilities = counts / total_samples;
mean_power = sum((unique_points .^ 2) .* probabilities);
scaling_factor = sqrt(mean_power);
if M == 4
data = data ./ sqrt(2.5); % 7-level constellation weighted with probability after DB code i.e. mean([-3 3 -2 -2 2 2 -1 -1 -1 1 1 1 0 0 0 0].^2) = 2.5 --> sqrt(2.5) == rms(constellation)
elseif M == 6

2
Classes/04_DSP/Equalizer/EQ.m
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@@ -1,4 +1,4 @@
classdef EQ
classdef EQ %< handle
%EQ Summary of this class goes here
% Detailed explanation goes here

2
Classes/Warehouse_class/classes/DataStorage.m
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@@ -129,7 +129,7 @@ classdef DataStorage < handle
tmp = obj.sto.(storageVarName){lin_idx(i)};
if ~isempty(tmp)
if isa(tmp,'Signal') || isa(tmp,'struct') || isa(tmp,'Exfo_laser')
if isa(tmp,'Signal') || isa(tmp,'struct') || isa(tmp,'Exfo_laser') || isa(tmp,'DC_supply')
if i == 1
value = {};
end

2
Functions/showCurrentMeasurement.m
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@@ -41,7 +41,7 @@ function showCurrentMeasurement(varargin)
for i = 1:length(values)
varNameLower = names{i}; % Convert variable name to lowercase for case-insensitive comparison
if isnumeric(values{i})
if any(contains(varNameLower, {'ber','mlse','ffe','db'}))
if any(contains(varNameLower, {'ber','mlse','ffe','db'},"IgnoreCase",true))
% Format 'ber' values in exponential notation with two decimal places
values{i} = sprintf('%.2e', values{i});
else

41
Tests/04_DSP/Coding/Duobinary_test.m
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@@ -12,9 +12,9 @@ classdef Duobinary_test < matlab.unittest.TestCase
properties (MethodSetupParameter)
% Define method-level parameters for PRBS and bit pattern
% i.e.: useprbs = {0,1};
useprbs = struct('true', 1,'false', 0); % variations: {0, 1}
useprbs = struct('true', 1); % variations: {0, 1}
M = struct('M2', 2, 'M4', 4, 'M6', 6, 'M8', 8); % variations: {2, 4, 6, 8}
O = struct('O10', 10,'O11', 11,'O12', 12,'O13', 13, 'O15', 15, 'O17', 17); % variations: {10, 15, 17}
O = struct('O10', 10,'O11', 11,'O12', 12,'O13', 13, 'O15', 15, 'O17', 17, 'O18', 18, 'O19', 19); % variations: {10, 15, 17}
end
properties (TestParameter)
@@ -31,14 +31,42 @@ classdef Duobinary_test < matlab.unittest.TestCase
fsym = round(datarate / log2(M)) ;
%%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
N = 2^O; %length of prbs
N = 2^(O-1); %length of prbs
[~,seed] = prbs(O,1); %initialize first seed of prbs
bitpattern=[];
if useprbs
for i = 1:log2(M)
[bitpattern(:,i),seed] = prbs(O,N,seed);
%%%%% MOVE-IT PRMS %%%%
state = struct();
para = struct();
if M == 6
para.bl = 2^(O-2);
para.dimension = 5;
else
para.bl = 2^(O-1);
para.dimension = log2(M); %2.5bits/sym -> 2 bit/sym
end
para.rand = 0;
para.order = floor(O / log2(M));
para.skip =0;
para.bruijn = 0;
para.reset_prms = 0;
para.method = 1;
data_in = [];
global loop;
loop = 0;
[data_out,state_] = prms(data_in, state, para);
loop = 1;
[data_out,state_out] = prms(data_in, state_, para);
bitpattern = data_out';
%%%%% END MOVE-IT %%%%%%%
else
s = RandStream('twister','Seed',randkey);
for i = 1:log2(M)
@@ -46,8 +74,9 @@ classdef Duobinary_test < matlab.unittest.TestCase
end
end
if M == 6
bitpattern = reshape(bitpattern,[],1);
bitpattern = reshape(bitpattern',[],1);
bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
end

80
projects/HighSpeedExperiment_2024/master_auswertung_10km.m Normal file
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@@ -0,0 +1,80 @@
wh = load('C:\Users\sioe\Documents\High_Speed_Measurement_2024\10km_bitrate_complete\20241030_170224_wh.mat');
wh = wh.obj;
M_vals = wh.parameter.M.values;
M_choose = M_vals(1);
lambda_vals = wh.parameter.lambda.values;
bitrate_vals = wh.parameter.bitrate.values;
duobinary_vals = wh.parameter.duobinary.values;
rop_atten_vals = wh.parameter.rop_atten.values;
figure(177)
for M_choose = [8]
sgtitle(['PAM',num2str(M_choose)])
for l = 1:numel(lambda_vals)
for b = 1:numel(bitrate_vals)
cel = wh.getStoValue('ber_vnle',M_choose(1),lambda_vals(l),bitrate_vals(b),duobinary_vals(1),rop_atten_vals(1));
ber_vnle(b)=min(cel{1});
cel = wh.getStoValue('ber_vnle_mlse',M_choose(1),lambda_vals(l),bitrate_vals(b),duobinary_vals(1),rop_atten_vals(1));
ber_vnle_mlse(b)=min(cel{1});
cel = wh.getStoValue('ber_db',M_choose(1),lambda_vals(l),bitrate_vals(b),duobinary_vals(2),rop_atten_vals(1));
ber_db(b)=min(cel{1});
cel = wh.getStoValue('ber_db',M_choose(1),lambda_vals(l),bitrate_vals(b),duobinary_vals(3),rop_atten_vals(1));
ber_db_enc(b)=min(cel{1});
dcs_ = wh.getStoValue('dcs',M_choose(1),lambda_vals(l),bitrate_vals(b),duobinary_vals(2),rop_atten_vals(1));
end
cols = linspecer(4);
subplot(3,3,l)
if M_choose == 4
lst = '-';
mkr = 'o';
hv = 'on';
elseif M_choose == 6
lst = '-';
mkr = 'x';
hv = 'on';
elseif M_choose == 8
lst = '-';
mkr = 'diamond';
hv = 'on';
end
fsym_vals = floor( bitrate_vals*1e-9./log2(M_choose) );
hold on
plot(bitrate_vals*1e-9,ber_db,'Color',cols(1,:),'Marker',mkr,'MarkerFaceColor','auto','DisplayName','DB pre','LineStyle',lst,'HandleVisibility',hv);
plot(bitrate_vals*1e-9,ber_db_enc,'Color',cols(2,:)','Marker',mkr,'MarkerFaceColor','auto','DisplayName','DB enc','LineStyle',lst,'HandleVisibility',hv);
plot(bitrate_vals*1e-9,ber_vnle,'Color',cols(3,:),'Marker',mkr,'MarkerFaceColor','auto','DisplayName','VNLE','LineStyle',lst,'HandleVisibility',hv);
plot(bitrate_vals*1e-9,ber_vnle_mlse,'Color',cols(4,:),'Marker',mkr,'MarkerFaceColor','auto','DisplayName','VNLE+PF+MLSE','LineStyle',lst,'HandleVisibility',hv);
% Continue with the rest of your plot settings
yline(3.8e-3, 'DisplayName', 'HD-FEC', 'LineStyle', '--', 'HandleVisibility', 'off');
yline(2e-2, 'DisplayName', '20%', 'LineStyle', '--','LineWidth',1, 'HandleVisibility', 'off');
xlabel('Bitrate');
ylabel('Bit Error Rate (BER)');
title([num2str(lambda_vals(l)),' nm']);
set(gca, 'yscale', 'log');
set(gca, 'Box', 'on');
grid on;
grid minor;
legend('Interpreter', 'none','Location','southwest');
ylim([1e-4,1e-1]);
xlim([bitrate_vals(1)*1e-9,bitrate_vals(end)*1e-9])
end
end

317
projects/HighSpeedExperiment_2024/master_evaluation.m
View File

@@ -1,22 +1,24 @@
folderpath = 'C:\Users\sioe\Documents\High_Speed_Measurement_2024\8km_bitrate_rop_master\';
folderpath = 'C:\Users\sioe\Documents\High_Speed_Measurement_2024\10km_bitrate_complete\';
experiment_name = '';
currentTime = datetime('now', 'Format', 'yyyyMMdd_HHmmss');
timeStr = char(currentTime);
experiment_name = [experiment_name, timeStr];
if 1
%%% BITRATE Sweep for MPI Experiment %%%
awg_vpp = 2.7;
pd_in_set = 8;
random_key = 0;
params = struct;
params.M = [4,6,8];
params.lambda = flip([1293, 1302, 1310, 1318, 1327.4]); %calcWavelengthPlan(16, 400e9 , 1310);
params.bitrate = [300:30:480].*1e9;
params.duobinary = [0,1];
params.M = [8];
params.lambda = [1293, 1297.5, 1302, 1306.5, 1310, 1313.4, 1318, 1322.7, 1327.4]; %calcWavelengthPlan(16, 400e9 , 1310);
params.bitrate = [270,300,330,360,390,400,410,420,430,440,450,460,470,480].*1e9;
params.duobinary = [0,1,2];
params.rop_atten = [0];
end
if 0
@@ -51,6 +53,8 @@ wh.addStorage("dcs");
wh.addStorage("pdfa");
wh.addStorage("exfo");
wh.addStorage("voa");
wh.addStorage("filename");
precomp_path = "C:\Users\sioe\Documents\High_Speed_Measurement_2024\precomp\";
precomp_fn = "lab_high_speed";
@@ -72,28 +76,91 @@ estimatedTotalTime = 0;
for M = wh.parameter.M.values
dcs = DC_supply("active",[1,0],"voltage",[2.3, 0]);
if M == 4
for db = wh.parameter.duobinary.values
if db == 1
ffe_only = 0;
postfilter_approach = 0;
db_channel_approach = 1;
db_coding_approach = 0;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -50;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
%pause(7*60); %wait 30 minutes for stable bias
v_bias_for_pam=2.3;
pulsef=0;
precomp_amp_max = -50;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 0;
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -50;
v_bias_for_pam=2.6;
dcs.set("voltage",[v_bias_for_pam, 0]);
pause(7*60); %wait 30 minutes for stable bias
pulsef = 0;
end
elseif db == 2
ffe_only = 0;
postfilter_approach = 0;
db_channel_approach = 0;
db_coding_approach = 1;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
pulsef=0;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
end
elseif db == 0
ffe_only = 0;
postfilter_approach = 1;
db_channel_approach = 0;
db_coding_approach = 0;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -37;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
pulsef=0;
precomp_amp_max = -34;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -34;
v_bias_for_pam=2.6;
dcs.set("voltage",[v_bias_for_pam, 0]);
pause(7*60); %wait 30 minutes for stable bias
pulsef = 0;
end
end
for lambda = wh.parameter.lambda.values
@@ -114,52 +181,13 @@ for M = wh.parameter.M.values
pdfa.enablePDFA();
% 4)
pdfa.setPumpLevel(100);
pdfa.setPumpLevel(86);
end
for bitrate = wh.parameter.bitrate.values
fsym = floor( bitrate*1e-9./log2(M) ).*1e9;
for db = wh.parameter.duobinary.values
if db == 1
ffe_only = 0;
postfilter_approach = 0;
db_channel_approach = 1;
db_coding_approach = 0;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -50;
elseif M == 6
pulsef=0;
precomp_amp_max = -50;
elseif M == 8
pulsef=0;
precomp_amp_max = -50;
end
elseif db == 0
ffe_only = 0;
postfilter_approach = 1;
db_channel_approach = 0;
db_coding_approach = 0;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -38;
elseif M == 6
pulsef=0;
precomp_amp_max = -34;
elseif M == 8
pulsef=0;
precomp_amp_max = -34;
end
end
%%%%% Construct AWG and Scope Modules %%%%%%
fdac = 256e9;
fadc = 256e9;
@@ -174,7 +202,7 @@ for M = wh.parameter.M.values
Pamsource = PAMsource(...
"fsym",fsym,"M",M,"order",19,"useprbs",1,...
"fs_out",fdac,...
"applyclipping",0,"clipfactor",1.5,...
"applyclipping",0,"clipfactor",1.2,...
"applypulseform",pulsef,"pulseformer",Pform,...
"randkey",random_key,...
"db_precode",db_precode,"db_encode",db_coding_approach,...
@@ -182,19 +210,39 @@ for M = wh.parameter.M.values
[Digi_sig,Symbols,Bits] = Pamsource.process();
% Digi_sig.plot("displayname","Digi_sig clipped","fignum",21,"clear",1);
%%%%% Precompensation Routine %%%%%%
if precomp_mode == 1 % measure channel
precomp_est = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',fdac);
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',fdac);
Digi_sig = precomp_est.buildOFDM();
elseif precomp_mode == 2 % apply precomp
precomp_est = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',Digi_sig.fs);
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
Digi_sig = precomp_est.precomp(Digi_sig,'maxampdb',precomp_amp_max,'loadPath',precomp_path,'fileName',precomp_fn);
end
%%%%% Resample to DAC rate %%%%%%
Digi_sig = Digi_sig.resample("fs_out",AWG.fdac);
% Digi_sig.spectrum("displayname","TX After precomp","fignum",30,"normalizeToNyquist",0,"normalizeTo0dB",1);
% Digi_sig.spectrum("displayname","TX After precomp","fignum",222,"normalizeToNyquist",0,"normalizeTo0dB",1);
if 0 %negative performance...
% X: design FIR filter for sinc precomp
% https://www.dsprelated.com/showarticle/1191.php
ntaps = 13;
npts = 32;
% least-squares FIR design
fmax = AWG.fdac*0.5;
ff = linspace(0,fmax,npts);
hsinc = sin(pi*ff/AWG.fdac)./(pi*ff/AWG.fdac + eps); % transfer function of sample and hold DAC
hsinc(1) = 1;
h_goal= 1./hsinc; % goal function
f = 2.*ff./AWG.fdac; %vector between 0 and 1, where 1 is nyquist is fsamp/2
b = firls(ntaps-1,f,h_goal);
Digi_sig.signal = conv(Digi_sig.signal,b,"same");
end
% Digi_sig.spectrum("displayname","TX After SINC precomp","fignum",222,"normalizeToNyquist",0,"normalizeTo0dB",1);
for rop_atten = wh.parameter.rop_atten.values
@@ -224,12 +272,12 @@ for M = wh.parameter.M.values
%%%%% AWG --> Scope %%%%%%
[~,Scpe_sig_raw,~,D] = A2S.process("signal2",Digi_sig,"waitUntilClick",0);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
save([folderpath,experiment_name,loop_name,'_raw_signal'],"Scpe_sig_raw");
% Scpe_sig_raw = Filter('filtdegree',5,"f_cutoff",0.55.*fsym,"fs",fadc,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig_raw);
%
% Scpe_sig_raw.plot("displayname","Scope raw signal","fignum",20,"clear",1);
Scpe_sig_raw.plot("displayname","Scope raw signal","fignum",20,"clear",1);
% Scpe_sig_raw.spectrum("displayname","Scope PSD","fignum",30,"normalizeTo0dB",1);
% Scpe_sig_raw.eye(fsym,M,"displayname",'eye','fignum',200);
@@ -252,7 +300,7 @@ for M = wh.parameter.M.values
%%%%% Plot and Save Routines: SAVE RECEIVED SIGNALS %%%%%%%%%%%%%%%%%%%%%%%%%
save([folderpath,experiment_name,loop_name,'_rx_signal'],"S");
save([folderpath,experiment_name,loop_name,'_raw_signal'],"Scpe_sig_raw");
%%%%% EQUALIZE %%%%%%
% set to minus one not zero not avoid confusion if BER is acutally zero
@@ -264,39 +312,20 @@ for M = wh.parameter.M.values
ffe = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
vnle = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if postfilter_approach %%%%%%%%%%%%%%%%%%%%%%%%%%%
if 1
eq_values = min(numel(S),8);
Noi = cell(eq_values,1);
EQ_vnle= cell(eq_values,1);
EQ_ffe= cell(eq_values,1);
if 0
parfor s = 1:eq_values
if 0
%FFE LINEAR
Scpe_sig_syncd = S{s};
[EQ_ffe{s}] = ffe.process(Scpe_sig_syncd,Symbols);
Noi{s} = EQ_ffe{s}-Symbols;
Rx_bits = PAMmapper(M,0).demap(EQ_ffe{s});
[~,~,ber_ffe(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
if 0
%FFE + MLSE
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
EQ_ffe{s} = EQ_ffe{s}.filter(burg_coeff,1);
EQ_mlse = MLSE("DIR",burg_coeff,"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_ffe{s});
Rx_bits = PAMmapper(M,0).demap(EQ_mlse);
[~,~,ber_ffe_mlse(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
if 1
%VNLE
vnle = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
Scpe_sig_syncd = S{s};
[EQ_vnle{s}] = vnle.process(Scpe_sig_syncd,Symbols);
Noi{s} = EQ_vnle{s}-Symbols;
@@ -306,6 +335,7 @@ for M = wh.parameter.M.values
%VNLE + MLSE
if 1
Noi{s}.signal = Noi{s}.signal - mean(Noi{s}.signal);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
EQ_mlse = EQ_vnle{s}.filter(burg_coeff,1);
@@ -317,22 +347,29 @@ for M = wh.parameter.M.values
end
disp(['FFE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe)),' WORST:',sprintf('%.1E',max(ber_ffe)),'. Out of ',num2str(numel(ber_ffe))]);
disp(['FFE + MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe_mlse)),' WORST:',sprintf('%.1E',max(ber_ffe_mlse)),'. Out of ',num2str(numel(ber_ffe_mlse))]);
disp(['VNLE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle)),' WORST:',sprintf('%.1E',max(ber_vnle)),'. Out of ',num2str(numel(ber_vnle))]);
disp(['VNLE+MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle_mlse)),' WORST:',sprintf('%.1E',max(ber_vnle_mlse)),'. Out of ',num2str(numel(ber_ffe))]);
if 0
[~,s]=min(ber_vnle_mlse);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
Noi{s}.spectrum('displayname','Noise PSD','fignum',123);
[h,w] = freqz(1,burg_coeff,length(Noi{s}),"whole",Noi{s}.fs);
h = h/max(abs(h));
hold on
w_ = (w - Noi{s}.fs/2);
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
end
[~,i] = min(ber_vnle);
figure(56);
if 0
figure(55);
clf
title(sprintf('PAM %d ; BER: %1.2e',M, ber_vnle(i)));
title(sprintf('PAM %d ; BER: %1.2e',M, ber_vnle_mlse(s) ));
constellation = unique(Symbols.signal);
received = NaN(numel(constellation),length(Symbols));
for lvl = 1:numel(constellation)
%Separate the equalized signal into the
%respective levels based on the actually
%transmitted level!
received(lvl,Symbols.signal==constellation(lvl)) = EQ_vnle{i}.signal(Symbols.signal==constellation(lvl));
received(lvl,Symbols.signal==constellation(lvl)) = EQ_vnle{s}.signal(Symbols.signal==constellation(lvl));
intermediate = received(lvl,:);
cnt(lvl) = numel(intermediate(~isnan(intermediate)));
hold on
@@ -341,52 +378,118 @@ for M = wh.parameter.M.values
legend
end
% disp(['FFE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe)),' WORST:',sprintf('%.1E',max(ber_ffe)),'. Out of ',num2str(numel(ber_ffe))]);
% disp(['FFE + MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe_mlse)),' WORST:',sprintf('%.1E',max(ber_ffe_mlse)),'. Out of ',num2str(numel(ber_ffe_mlse))]);
disp(['VNLE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle)),' WORST:',sprintf('%.1E',max(ber_vnle)),'. Out of ',num2str(numel(ber_vnle))]);
% disp(['VNLE+MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle_mlse)),' WORST:',sprintf('%.1E',max(ber_vnle_mlse)),'. Out of ',num2str(numel(ber_vnle_mlse))]);
end
elseif db_channel_approach %%%%%%%%%%%%%%%%%%%%%%%%%%%
ffe = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if 0
parfor s = 1:numel(S)
if 1
eq_values = min(numel(S),8);
Noi = cell(eq_values,1);
EQ_sig = cell(eq_values,1);
parfor s = 1:eq_values
Scpe_sig_syncd = S{s};
[EQ_sig, Noi] = ffe.process(Scpe_sig_syncd,Duobinary().encode(Symbols));
[EQ_sig{s}, Noi{s}] = ffe.process(Scpe_sig_syncd,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{s}.signal = EQ_sig{s}.signal-mean(EQ_sig{s}.signal);
EQ_sig = Duobinary().decode(EQ_sig);
EQ_sig_mlse = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_sig{s});
Rx_bits = PAMmapper(M,0).demap(EQ_sig);
EQ_sig_mlse = Duobinary().decode(EQ_sig_mlse);
Rx_bits = PAMmapper(M,0).demap(EQ_sig_mlse);
[~,num_errors,ber_db(s),pos_errors] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
if 0
[~,s]=min(ber_vnle_mlse);
Noi{s}.spectrum('displayname',['Noise; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
Duobinary().encode(Symbols).spectrum('displayname',['DB coded symbols; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
EQ_sig{s}.spectrum('displayname',['EQ; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
EQ_sig{s}.signal = EQ_sig{1}.signal-mean(EQ_sig{s}.signal);
end
disp(['DB EQ: BEST BER: ',sprintf('%.1E',min(ber_db)),' AVG BER: ',sprintf('%.1E',mean(ber_db)),' WORST:',sprintf('%.1E',max(ber_db)),'. Out of',num2str(numel(ber_db))]);
else
disp('Disabled MLSE for DB in all cases, due to time in measurement loop')
% disp('Disabled MLSE for DB in all cases, due to time in measurement loop')
end
elseif db_coding_approach
parfor s = 1:numel(S)
S{s}=S{s}.normalize("mode","rms");
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
[EQ_sig, Noi] = ffe.process(S{s},Symbols);
EQ_sig.plot("displayname",'After EQ','fignum',112);
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);
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if 1
eq_values = min(numel(S),8);
Noi = cell(eq_values,1);
EQ_sig = cell(eq_values,1);
EQ_sig_mlse = cell(eq_values,1);
parfor s = 1:eq_values
[EQ_sig{s}, Noi{s}] = ffe.process(S{s},Symbols);
EQ_sig_mlse{s} = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_sig{s});
EQ_sig_mlse{s} = Duobinary().decode(EQ_sig_mlse{s});
Rx_bits = PAMmapper(M,0).demap(EQ_sig_mlse{s});
[~,num_errors,ber_db(s),pos_errors] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
disp(['DB EQ: BEST BER: ',sprintf('%.1E',min(ber_db)),' AVG BER: ',sprintf('%.1E',mean(ber_db)),' WORST:',sprintf('%.1E',max(ber_db)),'. Out of',num2str(numel(ber_db))]);
if 1
[~,s]=min(ber_db);
Noi{s}.spectrum('displayname',['Noise '],'fignum',50,'normalizeTo0dB',1);
EQ_sig{s}.spectrum('displayname',['EQLZD '],'fignum',50,'normalizeTo0dB',1);
Symbols.spectrum('displayname',['Symbols '],'fignum',222,'normalizeTo0dB',1);
end
if 1
figure(51);
clf
title(sprintf('DB coded PAM after EQ ; BER: %1.2e',M, ber_db(s) ));
constellation = unique(Symbols.signal);
received = NaN(numel(constellation),length(Symbols));
for lvl = 1:numel(constellation)
%Separate the equalized signal into the
%respective levels based on the actually
%transmitted level!
received(lvl,Symbols.signal==constellation(lvl)) = EQ_sig{s}.signal(Symbols.signal==constellation(lvl));
intermediate = received(lvl,:);
cnt(lvl) = numel(intermediate(~isnan(intermediate)));
hold on
histogram(received(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' | ',num2str(cnt(lvl)),' entries']);
end
legend
end
end
end
% showCurrentMeasurement('Vbias', v_bias_for_pam,'MIN BER', min(ber_db),'MEAN BER',mean(ber_db),'MAX BER',max(ber_db), 'Fsym',fsym.*1e-9, 'ROP', rop, 'Precomp MaxAmp',precomp_amp_max);
%%%%% Store measurement into measurement "warehouse" %%%%%%
@@ -408,6 +511,8 @@ for M = wh.parameter.M.values
wh.addValueToStorage(ffe,'FFE',M,lambda,bitrate,db,rop_atten);
wh.addValueToStorage(vnle,'VNLE',M,lambda,bitrate,db,rop_atten);
wh.addValueToStorage(string([experiment_name,loop_name]),'filename',M,lambda,bitrate,db,rop_atten);
iterationTimes(loopcnt) = toc(iterationStartTime);
averageTimePerIteration = mean(iterationTimes(1:loopcnt));

267
projects/HighSpeedExperiment_2024/mpi_measurement.m
View File

@@ -1,6 +1,6 @@
folderpath = 'C:\Users\sioe\Documents\High_Speed_Measurement_2024\mpi_measurement\';
experiment_name = 'testen';
folderpath = 'C:\Users\sioe\Documents\High_Speed_Measurement_2024\MPI_duobinary_encoded\';
experiment_name = '';
currentTime = datetime('now', 'Format', 'yyyyMMdd_HHmmss');
timeStr = char(currentTime);
experiment_name = [experiment_name, timeStr];
@@ -16,10 +16,10 @@ pd_in_set = 8; %VOA 2 -> PD in
random_key = 0;
params = struct;
params.M = [8];
params.bitrate = [336].*1e9;%[90:60:480].*1e9;%[300:30:480].*1e9;
params.duobinary = [0];
params.interference_atten = [45];
params.M = [4];
params.bitrate = [336,360,390,420,448].*1e9;%[90:60:480].*1e9;%[300:30:480].*1e9;
params.duobinary = [2];
params.interference_atten = [0:1:20,45];
wh = DataStorage(params);
@@ -38,7 +38,7 @@ wh.addStorage("s_power");
wh.addStorage("i_power");
wh.addStorage("sir");
wh.addStorage("filename");
wh.addStorage("m");
wh.addStorage("dcs");
@@ -66,37 +66,13 @@ estimatedTotalTime = 0;
for M = wh.parameter.M.values
dcs = DC_supply("active",[1,0],"voltage",[2.3, 0]);
if M == 4
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
%pause(7*60); %wait 30 minutes for stable bias
v_bias_for_pam=2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 0;
elseif M == 8
v_bias_for_pam=2.6;
dcs.set("voltage",[v_bias_for_pam, 0]);
disp('waiting...');
%pause(5*60); %wait 5 minutes for stable bias
pulsef = 0;
end
for bitrate = wh.parameter.bitrate.values
fsym = floor( bitrate*1e-9./log2(M) ).*1e9;
for db = wh.parameter.duobinary.values
dcs = DC_supply("active",[1,0],"voltage",[2.3, 0]);
if db == 1
ffe_only = 0;
postfilter_approach = 0;
@@ -106,13 +82,50 @@ for M = wh.parameter.M.values
if M == 4
pulsef=1;
precomp_amp_max = -50;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
pulsef=0;
precomp_amp_max = -50;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -50;
v_bias_for_pam=2.6;
dcs.set("voltage",[v_bias_for_pam, 0]);
pause(7*60); %wait 30 minutes for stable bias
pulsef = 0;
end
elseif db == 2
ffe_only = 0;
postfilter_approach = 0;
db_channel_approach = 0;
db_coding_approach = 1;
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
pulsef=0;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -38;
v_bias_for_pam = 2.8;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
end
elseif db == 0
ffe_only = 0;
postfilter_approach = 1;
@@ -121,13 +134,23 @@ for M = wh.parameter.M.values
db_precode = db_coding_approach || db_channel_approach;
if M == 4
pulsef=1;
precomp_amp_max = -38;
precomp_amp_max = -37;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 6
pulsef=0;
precomp_amp_max = -34;
v_bias_for_pam = 2.3;
dcs.set("voltage",[v_bias_for_pam, 0]);
pulsef = 1;
elseif M == 8
pulsef=0;
precomp_amp_max = -34;
v_bias_for_pam=2.6;
dcs.set("voltage",[v_bias_for_pam, 0]);
pause(7*60); %wait 30 minutes for stable bias
pulsef = 0;
end
end
@@ -161,24 +184,23 @@ for M = wh.parameter.M.values
end
%%%%% Resample to DAC rate %%%%%%
Digi_sig = Digi_sig.resample("fs_out",AWG.fdac);
Digi_sig = Digi_sig.resample("fs_out",fdac);
% Digi_sig = Filter('filtdegree',5,"f_cutoff",0.75*fsym,"fs",fadc,"filterType",filtertypes.gaussian,"active",true).process(Digi_sig);
% Digi_sig.spectrum("displayname","TX After precomp","fignum",10,"normalizeToNyquist",0,"normalizeTo0dB",0);
holdAndShowValue;
% holdAndShowValue;
scopeAutoScale = 1;
for interference_atten = wh.parameter.interference_atten.values
SCP = ScopeKeysight("model","UXR1104B",'autoscale',scopeAutoScale,"fadc","GSa_256","channel",[0,1,0,0],"recordLen",10000000,"removeDC",1);
SCP = ScopeKeysight("model","UXR1104B",'autoscale',scopeAutoScale,"fadc","GSa_256","channel",[0,1,0,0],"recordLen",6000000,"removeDC",1);
AWG = AwgKeysight("model","M8199B","fdac",fdac,"scaletodac",[1,1],"skews",[0,0],"voltages",[0,awg_vpp]);
A2S = Awg2Scope(AWG,SCP,[0,2,0,0],"waitUntilClick",1); %
scopeAutoScale = 0; %until is set to 1 in next db change and then bitrate
% scopeAutoScale = 0; %until is set to 1 in next db change and then bitrate
%%%%% Loop Preps
iterationStartTime = tic;
@@ -204,35 +226,34 @@ for M = wh.parameter.M.values
%%%%% AWG --> Scope %%%%%%
[~,Scpe_sig_raw,~,D] = A2S.process("signal2",Digi_sig,"waitUntilClick",0);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Scpe_sig_raw.spectrum("displayname","Scope PSD before filter","fignum",30,"normalizeTo0dB",1);
Scpe_sig_raw = Filter('filtdegree',5,"f_cutoff",0.65.*fsym,"fs",fadc,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig_raw);
% Scpe_sig_raw.spectrum("displayname","Scope PSD after filter","fignum",30,"normalizeTo0dB",1);
%%%%%% Sample to 2x fsym %%%%%%
Scpe_sig_resampled = Scpe_sig_raw.resample("fs_in",fadc,"fs_out",2*fsym);
save([folderpath,experiment_name,loop_name,'_raw_signal'],"Scpe_sig_raw");
voa.readvals();
rop = voa.power_state(1);
pd_in = voa.power_state(2);
i_power = voa.power_state(4);
s_power = voa.power_state(3);
sir = s_power-i_power;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Scpe_sig_raw.spectrum("displayname","Scope PSD before filter","fignum",30,"normalizeTo0dB",1);
% Scpe_sig_raw = Filter('filtdegree',5,"f_cutoff",0.65.*fsym,"fs",fadc,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig_raw);
% Scpe_sig_raw.spectrum("displayname","Scope PSD after filter","fignum",30,"normalizeTo0dB",1);
%%%%%% Sample to 2x fsym %%%%%%
Scpe_sig_resampled = Scpe_sig_raw.resample("fs_in",fadc,"fs_out",2*fsym);
Scpe_sig_raw.plot("displayname",['SIR: ',sprintf('%.2f',sir),' dB'],"fignum",20,"clear",1);
disp(['PDin: ',sprintf('%.2f',pd_in),' dB | S: ',sprintf('%.2f',s_power),' dB | I: ',sprintf('%.2f',i_power),' dB | -> SIR: ',sprintf('%.2f',sir),' dB']);
% disp(['PDin: ',sprintf('%.2f',pd_in),' dB | S: ',sprintf('%.2f',s_power),' dB | I: ',sprintf('%.2f',i_power),' dB | -> SIR: ',sprintf('%.2f',sir),' dB']);
%%%%%% Sync Rx signal with reference (S is a cell array with all occurences) %%%%%%
[Scpe_sig_syncd,S,isFlipped] = Scpe_sig_resampled.tsynch("reference",Symbols,"fs_ref",fsym);
%%%%% Plot and Save Routines: SAVE RECEIVED SIGNALS %%%%%%%%%%%%%%%%%%%%%%%%%
save([folderpath,experiment_name,loop_name,'_rx_signal'],"S");
save([folderpath,experiment_name,loop_name,'_raw_signal'],"Scpe_sig_raw");
%%%%% EQUALIZE %%%%%%
% set to minus one not zero not avoid confusion if BER is acutally zero
@@ -244,7 +265,6 @@ for M = wh.parameter.M.values
ffe = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
vnle = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if postfilter_approach %%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -256,29 +276,9 @@ for M = wh.parameter.M.values
EQ_ffe= cell(eq_values,1);
parfor s = 1:eq_values
if 0
%FFE LINEAR
Scpe_sig_syncd = S{s};
[EQ_ffe{s}] = ffe.process(Scpe_sig_syncd,Symbols);
Noi{s} = EQ_ffe{s}-Symbols;
Rx_bits = PAMmapper(M,0).demap(EQ_ffe{s});
[~,~,ber_ffe(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
if 0
%FFE + MLSE
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
EQ_ffe{s} = EQ_ffe{s}.filter(burg_coeff,1);
EQ_mlse = MLSE("DIR",burg_coeff,"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_ffe{s});
Rx_bits = PAMmapper(M,0).demap(EQ_mlse);
[~,~,ber_ffe_mlse(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
if 1
%VNLE
vnle = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
Scpe_sig_syncd = S{s};
[EQ_vnle{s}] = vnle.process(Scpe_sig_syncd,Symbols);
Noi{s} = EQ_vnle{s}-Symbols;
@@ -288,6 +288,7 @@ for M = wh.parameter.M.values
%VNLE + MLSE
if 1
Noi{s}.signal = Noi{s}.signal - mean(Noi{s}.signal);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
EQ_mlse = EQ_vnle{s}.filter(burg_coeff,1);
@@ -298,29 +299,50 @@ for M = wh.parameter.M.values
end
end
if 0
nc=1;
Noi{1}.spectrum('displayname',['Noise; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
burg_coeff = arburg(Noi{1}.signal,nc);
[h,w] = freqz(1,burg_coeff,length(Noi{1}),"whole",Noi{1}.fs);
if 1
[~,s]=min(ber_vnle_mlse);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
Noi{s}.spectrum('displayname','Noise PSD','fignum',123);
[h,w] = freqz(1,burg_coeff,length(Noi{s}),"whole",Noi{s}.fs);
h = h/max(abs(h));
hold on
w_ = (w - Noi{1}.fs/2);
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',[num2str(nc), ' burg; SIR:',sprintf('%.2f',sir)]);
drawnow;
w_ = (w - Noi{s}.fs/2);
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
end
if 1
figure(55);
clf
title(sprintf('PAM %d ; BER: %1.2e',M, ber_vnle_mlse(s) ));
constellation = unique(Symbols.signal);
received = NaN(numel(constellation),length(Symbols));
for lvl = 1:numel(constellation)
%Separate the equalized signal into the
%respective levels based on the actually
%transmitted level!
received(lvl,Symbols.signal==constellation(lvl)) = EQ_vnle{s}.signal(Symbols.signal==constellation(lvl));
intermediate = received(lvl,:);
cnt(lvl) = numel(intermediate(~isnan(intermediate)));
hold on
histogram(received(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' | ',num2str(cnt(lvl)),' entries']);
end
legend
end
% disp(['FFE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe)),' WORST:',sprintf('%.1E',max(ber_ffe)),'. Out of ',num2str(numel(ber_ffe))]);
% disp(['FFE + MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_ffe_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_ffe_mlse)),' WORST:',sprintf('%.1E',max(ber_ffe_mlse)),'. Out of ',num2str(numel(ber_ffe_mlse))]);
disp(['VNLE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle)),' WORST:',sprintf('%.1E',max(ber_vnle)),'. Out of ',num2str(numel(ber_vnle))]);
% disp(['VNLE+MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle_mlse)),' WORST:',sprintf('%.1E',max(ber_vnle_mlse)),'. Out of ',num2str(numel(ber_vnle_mlse))]);
end
elseif db_channel_approach %%%%%%%%%%%%%%%%%%%%%%%%%%%
ffe = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if 0
@@ -346,24 +368,88 @@ for M = wh.parameter.M.values
end
if 0
Noi{1}.spectrum('displayname',['Noise; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
if 1
[~,s]=min(ber_vnle_mlse);
Noi{s}.spectrum('displayname',['Noise; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
Duobinary().encode(Symbols).spectrum('displayname',['DB coded symbols; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
EQ_sig{1}.spectrum('displayname',['EQ; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
EQ_sig{1}.signal = EQ_sig{1}.signal-mean(EQ_sig{1}.signal);
EQ_sig{s}.spectrum('displayname',['EQ; SIR:',sprintf('%.2f',sir)],'fignum',40,'normalizeTo0dB',1);
EQ_sig{s}.signal = EQ_sig{1}.signal-mean(EQ_sig{s}.signal);
end
disp(['DB EQ: BEST BER: ',sprintf('%.1E',min(ber_db)),' AVG BER: ',sprintf('%.1E',mean(ber_db)),' WORST:',sprintf('%.1E',max(ber_db)),'. Out of',num2str(numel(ber_db))]);
else
disp('Disabled MLSE for DB in all cases, due to time in measurement loop')
% disp('Disabled MLSE for DB in all cases, due to time in measurement loop')
end
elseif db_coding_approach
ffe = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
if 1
eq_values = min(numel(S),8);
Noi = cell(eq_values,1);
EQ_sig = cell(eq_values,1);
EQ_sig_mlse = cell(eq_values,1);
parfor s = 1:eq_values
[EQ_sig{s}, Noi{s}] = ffe.process(S{s},Symbols);
EQ_sig_mlse{s} = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_sig{s});
EQ_sig_mlse{s} = Duobinary().decode(EQ_sig_mlse{s});
Rx_bits = PAMmapper(M,0).demap(EQ_sig_mlse{s});
[~,num_errors,ber_db(s),pos_errors] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
disp(['DB EQ: BEST BER: ',sprintf('%.1E',min(ber_db)),' AVG BER: ',sprintf('%.1E',mean(ber_db)),' WORST:',sprintf('%.1E',max(ber_db)),'. Out of',num2str(numel(ber_db))]);
if 1
[~,s]=min(ber_db);
Noi{s}.spectrum('displayname',['Noise '],'fignum',50,'normalizeTo0dB',1);
EQ_sig{s}.spectrum('displayname',['EQLZD '],'fignum',50,'normalizeTo0dB',1);
Symbols.spectrum('displayname',['Symbols '],'fignum',50,'normalizeTo0dB',1);
nc = 5;
burg_coeff = arburg(Noi{s}.signal,nc);
[h,w] = freqz(1,burg_coeff,length(Noi{s}),"whole",Noi{s}.fs);
h = h/max(abs(h));
hold on
w_ = (w - Noi{s}.fs/2);
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
end
if 1
figure(51);
clf
title(sprintf('DB coded PAM after EQ ; BER: %1.2e',M, ber_db(s) ));
constellation = unique(Symbols.signal);
received = NaN(numel(constellation),length(Symbols));
for lvl = 1:numel(constellation)
%Separate the equalized signal into the
%respective levels based on the actually
%transmitted level!
received(lvl,Symbols.signal==constellation(lvl)) = EQ_sig{s}.signal(Symbols.signal==constellation(lvl));
intermediate = received(lvl,:);
cnt(lvl) = numel(intermediate(~isnan(intermediate)));
hold on
histogram(received(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' | ',num2str(cnt(lvl)),' entries']);
end
legend
end
end
end
showCurrentMeasurement('Att.',interference_atten,'SIR',sir,'MIN BER', min(ber_db),'MEAN BER',mean(ber_db),'MAX BER',max(ber_db), 'Fsym',fsym.*1e-9, 'ROP', rop, 'Precomp MaxAmp',precomp_amp_max);
%%%%% Store measurement into measurement "warehouse" %%%%%%
wh.addValueToStorage({ber_ffe},'ber_ffe',M,bitrate,db,interference_atten);
@@ -378,6 +464,8 @@ for M = wh.parameter.M.values
wh.addValueToStorage(i_power,'i_power',M,bitrate,db,interference_atten);
wh.addValueToStorage(sir,'sir',M,bitrate,db,interference_atten);
wh.addValueToStorage(string([experiment_name,loop_name]),'filename',M,bitrate,db,interference_atten);
wh.addValueToStorage(M,'m',M,bitrate,db,interference_atten);
wh.addValueToStorage(dcs,'dcs',M,bitrate,db,interference_atten);
@@ -402,13 +490,10 @@ for M = wh.parameter.M.values
wh.save([folderpath,experiment_name,'_wh']);
showCurrentMeasurement('SIR', sir, 'I Att', interference_atten,'BER V', min(ber_vnle),'BER M',min(ber_vnle_mlse),'BER DB',min(ber_db),'Fsym',fsym.*1e-9, 'ROP', rop, 'PAM',M);
end
end
end
end
close(hWaitbar);

97
projects/HighSpeedExperiment_2024/offline_dsp/mpi_dsp.m Normal file
View File

@@ -0,0 +1,97 @@
% Set your folder path here
folderPath = 'C:\Users\sioe\Documents\High_Speed_Measurement_2024\mpi_measurement\';
fileTimeStmp = 'testen20241028_163511';
fileBody = [fileTimeStmp,'_PAM_4_R_336000000000_DB_1_I_atten_'];
fileBits = [folderPath,fileBody,'0_bits'];
fileSymbols = [folderPath,fileBody,'0_symbols'];
fileWareHouse = [folderPath,fileTimeStmp,'_wh'];
Bits = load(fileBits,"Bits");Bits = Bits.Bits;
Symbols = load(fileSymbols);Symbols = Symbols.Symbols;
wh = load(fileWareHouse);wh = wh.obj;
M = wh.parameter.M.values(1);
cnt = 1;
for i_atten = 24%flip([0:3:30,45])
fileRx = [folderPath,fileBody,num2str(i_atten),'_rx_signal'];
S = load(fileRx);S = S.S;
Scpe_sig_raw = load([folderPath,fileBody,num2str(i_atten),'_raw_signal']);
Scpe_sig_raw = Scpe_sig_raw.Scpe_sig_raw;
Scpe_sig_raw.spectrum("displayname",'Raw signal','fignum',80,'normalizeTo0dB',1);
eq_values = min(numel(S),8);
Noi = cell(eq_values,1);
EQ_vnle= cell(eq_values,1);
EQ_ffe= cell(eq_values,1);
%ffe = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
vnle = EQ("Ne",[50,0,0],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.0,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
parfor s = 1:eq_values
if 1
%VNLE
Scpe_sig_syncd = S{s};
[EQ_vnle{s}] = vnle.process(Scpe_sig_syncd,Symbols);
Noi{s} = EQ_vnle{s}-Symbols;
Rx_bits = PAMmapper(M,0).demap(EQ_vnle{s});
[~,~,ber_vnle(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
%VNLE + MLSE
if 1
Noi{s}.signal = Noi{s}.signal - mean(Noi{s}.signal);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
EQ_mlse = EQ_vnle{s}.filter(burg_coeff,1);
EQ_mlse = MLSE("DIR",burg_coeff,"duobinary_output",0,"M",M,"trellis_states",PAMmapper(M,0).levels).process(EQ_mlse);
Rx_bits = PAMmapper(M,0).demap(EQ_mlse);
[~,~,ber_vnle_mlse(s),~] = calc_ber(Rx_bits.signal,Bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
end
end
if 1
[~,s]=min(ber_vnle_mlse);
nc = 2;
burg_coeff = arburg(Noi{s}.signal,nc);
Noi{s}.spectrum('displayname','Noise PSD','fignum',123);
[h,w] = freqz(1,burg_coeff,length(Noi{s}),"whole",Noi{s}.fs);
h = h/max(abs(h));
hold on
w_ = (w - Noi{s}.fs/2);
plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['', num2str(nc), ' coefficients for burg alg.']);
end
disp(['VNLE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle)),' WORST:',sprintf('%.1E',max(ber_vnle)),'. Out of ',num2str(numel(ber_vnle))]);
disp(['VNLE+MLSE EQ: BEST BER: ',sprintf('%.1E',min(ber_vnle_mlse)),' AVG BER: ',sprintf('%.1E',mean(ber_vnle_mlse)),' WORST:',sprintf('%.1E',max(ber_vnle_mlse)),'. Out of ',num2str(numel(ber_vnle_mlse))]);
vnle_result(cnt) = min(ber_vnle);
mlse_result(cnt) = min(ber_vnle_mlse);
cnt=cnt+1;
end
i_atten = flip([0:3:30,45]);
figure(90)
plot(i_atten,mlse_result);
% Continue with the rest of your plot settings
title('MPI')
yline(3.8e-3, 'DisplayName', 'HD-FEC', 'LineStyle', '--', 'HandleVisibility', 'off');
xlabel('Bit Rate in GBps');
ylabel('Attenuation of I Branch');
set(gca, 'yscale', 'log');
set(gca, 'Box', 'on');
grid on;
grid minor;
legend('Interpreter', 'none');