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This commit is contained in:
Silas Oettinghaus
2024-04-22 11:14:06 +02:00
parent ed17953407
commit cb54f4480e
10 changed files with 428 additions and 211 deletions
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28
Classes/00_signals/Signal.m
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@@ -364,6 +364,34 @@ classdef Signal
end
function eye(obj,fsym)
disp('h');
fsig = obj.fs;
q = fsig/fsym;
if q > 10
sig = abs(obj.signal).^2;
else
sig = abs(obj.resample("fs_in",fsig,"fs_out",fsym*10).signal);
q = 10;
end
figure(12)
clf
cursor = 200*q;
for s = 1:700
plot(sig(cursor-q:cursor+q),'Color','black','LineWidth',0.1,'LineStyle','-');
hold on
cursor=cursor+q;
s=s+1;
end
end
end
end

4
Classes/04_DSP/EQ.m
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@@ -384,7 +384,7 @@ classdef EQ
end
for dd_loop = 1:obj.dd_loops
cnt = obj.training_length+1;
cnt = 1;
m = 0;
output_vec = zeros(1,floor(length(data_in)/obj.K)); % initilaization of the output vector
dd_DFE = zeros(obj.Nb(1),1);
@@ -452,7 +452,7 @@ classdef EQ
% e_save(:,save_ind) = coeff;
% save_ind = save_ind+1;
if mu_mat ~= 0
if 1%mu_mat ~= 0
e_dc = e_dc - obj.DCmu*error;
error_log(cnt,dd_loop) = e_dc;
cnt = cnt+1;

63
Classes/04_DSP/EQ_silas.m
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@@ -111,12 +111,16 @@ classdef EQ_silas < handle
% actual processing of the signal (steps 1. - 3.)
% 1 normalize RMS
%signalclass_in = signalclass_in.normalize("mode","rms");
signalclass_in = signalclass_in.normalize("mode","rms");
% Process the EQ optimization
obj.process_(signalclass_in.signal', reference_signalclass_in.signal');
signalclass_in.signal = obj.y_out';
%change sampling frequency of outgoing signal
signalclass_in.fs = reference_signalclass_in.fs;
% append to logbook
lbdesc = ['EQ von Silas ist gelaufen '];
signalclass_in = signalclass_in.logbookentry(lbdesc);
@@ -198,6 +202,7 @@ classdef EQ_silas < handle
dc_cnt = 0;
end
end
end
@@ -209,11 +214,9 @@ classdef EQ_silas < handle
%start the dd mode with coefficients from training
coeff = [obj.e;obj.b];
obj.e_dc = ones(obj.eq_updatelatency,1).*obj.e_dc;
obj.e_dc = ones(obj.eq_updatelatency,1);%.*obj.e_dc;
dc_block = ones(obj.eq_parallelization_blocklength,1);
for ddloop = 1:obj.ddloops
m = 0;
@@ -261,7 +264,6 @@ classdef EQ_silas < handle
%combine FFE with DFE to one vector (cursor between the two sequences)
x_d = [x_vnle;-d_vnle];
%Apply filter
%y(m) = (m_reg(end)*dc_cnt + obj.e_dc(end)) + x_d.'* coeff;
if obj.mu_dc_dd > 0
@@ -270,13 +272,6 @@ classdef EQ_silas < handle
y(m) = x_d.'* coeff;
end
% if obj.eq_avg_blocklength > 0 %% Das läuft nicht gut!!
% averaging_window = circshift(averaging_window,obj.sps);
% averaging_window(1:obj.sps,1) = y(m);
% avg_(m) = mean(averaging_window);
% y(m) = y(m)-avg_(m);
% end
%Decision
[~,symbol_idx] = min(abs(y(m) - obj.d_constellation)); % decision for closest constellation point
d_hat(k) = obj.d_constellation(symbol_idx);
@@ -284,15 +279,8 @@ classdef EQ_silas < handle
%Error between FFE & DFE filtered signal and Decision
obj.error(k) = y(m) - d_hat(k);
% if obj.eq_avg_blocklength > 0 %% Das läuft nicht gut!!
% averaging_window = circshift(averaging_window,obj.sps);
% averaging_window(1:obj.sps,1) = y(m);
% avg_(m) = mean(averaging_window);
% y(m) = y(m)-avg_(m);
% end
%Update FFE and DFE coefficients
coeff = coeff - mu_mat*obj.error(k) * conj(x_d);
coeff = coeff - (mu_mat * (obj.error(k) * conj(x_d)));
%Update DC error
dc_block(dc_cnt) = obj.error(k) ;
@@ -313,6 +301,8 @@ classdef EQ_silas < handle
% obj.e_dc = obj.e_dc - sign(m_reg(end)) .* (sum(dc_block).* m_reg(end) .* obj.mu_dc_dd);
obj.e_dc = obj.e_dc - sum(dc_block) .* obj.mu_dc_dd;
% obj.e_dc = obj.e_dc - obj.mu_dc_dd * obj.error(k); %newapril
end
dc_cnt = 0;
@@ -343,24 +333,43 @@ classdef EQ_silas < handle
function x_in_vnle_format = calcVNLENonlinVecs(~,x_in_block,I_2,I_3,N_,norm_)
% These are the second and third order input signal products of the VNLE EQ
% ∑ h1 x_in(k-n1) + ∑∑ h2 x_in(k-n1)*x_in(k-n2) + ∑∑∑ h3 x_in(k-n1)*x_in(k-n2)*x_in(k-n3)
l1=length(x_in_block);
l2=length(I_2);
l3=length(I_3);
final_length = l1+l2+l3;
x1 = x_in_block;
x2 = [];
x3 = [];
x_in_vnle_format = zeros(final_length,1);
idx = l1;
x_in_vnle_format(1:idx) = x_in_block;
if N_(2) > 0
delta_2 = round((N_(1)-N_(2)) / 2);
input_vec_se = x_in_block(delta_2:end) / norm_(2); %TODO normalization step
x2 = input_vec_se(I_2(:,1)).*input_vec_se(I_2(:,2));
% Extract columns from I_2
col1 = input_vec_se(I_2(:,1));
col2 = input_vec_se(I_2(:,2));
x2 = col1 .* col2;
x_in_vnle_format(idx+1:idx+l2) = x2;
end
if N_(3) > 0
delta_3 = round((N_(1)-N_(3))/2);
input_vec_th = x_in_block(delta_3:end) / norm_(3);
x3 = input_vec_th(I_3(:,1)).*input_vec_th(I_3(:,2)).*input_vec_th(I_3(:,3));
end
x_in_vnle_format = [x1;x2;x3];
% Extract columns from I_3
col1 = input_vec_th(I_3(:,1));
col2 = input_vec_th(I_3(:,2));
col3 = input_vec_th(I_3(:,3));
% Perform matrix multiplication
x3 = col1 .* col2 .* col3;
idx = idx+l2;
x_in_vnle_format(idx+1:idx+l3) = x3;
end
end

33
Classes/04_DSP/EQ_silas_sliding_window_dc_removal.m
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@@ -293,24 +293,43 @@ classdef EQ_silas_sliding_window_dc_removal < handle
function x_in_vnle_format = calcVNLENonlinVecs(~,x_in_block,I_2,I_3,N_,norm_)
% These are the second and third order input signal products of the VNLE EQ
% ∑ h1 x_in(k-n1) + ∑∑ h2 x_in(k-n1)*x_in(k-n2) + ∑∑∑ h3 x_in(k-n1)*x_in(k-n2)*x_in(k-n3)
l1=length(x_in_block);
l2=length(I_2);
l3=length(I_3);
final_length = l1+l2+l3;
x1 = x_in_block;
x2 = [];
x3 = [];
x_in_vnle_format = zeros(final_length,1);
idx = l1;
x_in_vnle_format(1:idx) = x_in_block;
if N_(2) > 0
delta_2 = round((N_(1)-N_(2)) / 2);
input_vec_se = x_in_block(delta_2:end) / norm_(2); %TODO normalization step
x2 = input_vec_se(I_2(:,1)).*input_vec_se(I_2(:,2));
% Extract columns from I_2
col1 = input_vec_se(I_2(:,1));
col2 = input_vec_se(I_2(:,2));
x2 = col1 .* col2;
x_in_vnle_format(idx+1:idx+l2) = x2;
end
if N_(3) > 0
delta_3 = round((N_(1)-N_(3))/2);
input_vec_th = x_in_block(delta_3:end) / norm_(3);
x3 = input_vec_th(I_3(:,1)).*input_vec_th(I_3(:,2)).*input_vec_th(I_3(:,3));
end
x_in_vnle_format = [x1;x2;x3];
% Extract columns from I_3
col1 = input_vec_th(I_3(:,1));
col2 = input_vec_th(I_3(:,2));
col3 = input_vec_th(I_3(:,3));
% Perform matrix multiplication
x3 = col1 .* col2 .* col3;
idx = idx+l2;
x_in_vnle_format(idx+1:idx+l3) = x3;
end
end

2
Functions/calc_ber.m
View File

@@ -48,7 +48,7 @@ end
data_ = logical(data(skipstart+1:end-skip_end,:))';
delta_bits = length(reference) - length(data_);
delta_bits = length(reference) - length(data);
skip_end = max(skip_end,delta_bits);
reference_ = logical(reference(skipstart+1:end-skip_end,:))';

51
projects/MPI_April/auswertung_1.m Normal file
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@@ -0,0 +1,51 @@
vp = wh.parameter.vp.values(1);
vb = wh.parameter.vb.values(1);
rop = wh.parameter.rop.values;
f=figure(1113);
tiledlayout(2,4)
for sir = [20,36]
for lw = wh.parameter.laser_linewidth.values
nexttile
cols = linspecer(9);
cnt = 1;
for bias = wh.parameter.vb.values
curber = [];
curstd = [];
rop_meas = [];
txpow_meas = wh.getStoValue('mod_out_pow',sir,lw,1,vp,bias,rop(1));
for pn_key = wh.parameter.pn_key.values
curber(end+1,:) = wh.getStoValue('ber',sir,lw,pn_key,vp,bias,rop);
rop_meas(end+1,:) = wh.getStoValue('rop_save',sir,lw,pn_key,vp,bias,rop);
curstd(end+1,:,:) = wh.getStoValue('level_std',sir,lw,pn_key,vp,bias,rop);
plot(rop_meas(end,:)-txpow_meas, curber(end,:) ,'LineStyle',':','Color',cols(cnt,:),'LineWidth',0.1,'Marker','o','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',cols(cnt,:),'HandleVisibility','off','MarkerSize',1);
hold on
end
[wrst,idx]=max(curber);
for i = 1:numel(idx)
rop_wrst(i)=rop_meas(idx(i),i);
end
plot( rop_wrst-txpow_meas, wrst ,'LineStyle',':','Color',cols(cnt,:),'LineWidth',1,'Marker','^','MarkerSize',5,'MarkerEdgeColor',[1 1 1],'MarkerFaceColor',cols(cnt,:),'HandleVisibility','off');
plot(mean(rop_meas,1)-txpow_meas, mean(curber,1),'DisplayName',['Vbias: ',num2str(bias),' V'],'LineStyle','-','Color',cols(cnt,:),'LineWidth',1,'Marker','o','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',cols(cnt,:));
hold on
cnt = cnt+1;
end
title(['SIR: ',num2str(sir),'; Lw: ',num2str(lw*1e-6),' MHz; Vpeakpeak: ',num2str(2*vp)])
set(gca,'YScale','log');
legend('Location','southwest')
xlabel("measured ROP in dBm")
ylabel("BER")
yline(3.8e-3,'DisplayName','FEC');
xlim([-5,3]);
ylim([1e-4,3e-1]);
drawnow
end
end

202
projects/MPI_April/mpi_simulation_cspr.m
View File

@@ -4,20 +4,16 @@ clear
filename = '112G_2';
load_sequence = 0;
M = 4;
datarate = 112e9;
M = 8;
datarate = 448e9;
kover = 8;
kover = 4;
fsym = round(datarate*1e-9 / log2(M))*1e9;
%fsym = 50e9;
fdac = 256e9;
fadc = 256e9;
laser_linewidth = 1e6;
mpi_ = 50; %meter
sir = 20; %decibel = attenuation of interference path
lowpass_cutoff = fsym/2 * 1;
lowpass_cutoff = fsym/2 * 1.5;
awg_bw = lowpass_cutoff;
mod_bw = lowpass_cutoff;
phd_bw = lowpass_cutoff;
@@ -25,32 +21,18 @@ scp_bw = lowpass_cutoff;
mpi_path=50;
vp = [0.25];
vb = [0.5:0.05:0.8];
vb = 0.7;
pn_key = [27];
rop = -5;
LP_awg = Filter('filtdegree',2,"f_cutoff",awg_bw,"fs",fdac,"filterType","butterworth");
LP_awg = Filter('filtdegree',2,"f_cutoff",awg_bw,"fs",fdac*kover,"filterType","butterworth");
LP_laser = Filter('filtdegree',4,"f_cutoff",mod_bw,"fs",fdac*kover,"filterType",filtertypes.gaussian);
LP_opt = Filter('filtdegree',4,"f_cutoff",fsym/log2(M).*1.5,"fs",fdac*kover,"filterType",filtertypes.gaussian);
LP_phd = Filter('filtdegree',2,"f_cutoff",phd_bw,"fs",fdac*kover,"filterType",filtertypes.butterworth);
LP_scpe = Filter('filtdegree',2,"f_cutoff",scp_bw,"fs",fadc,"filterType","butterworth");
for pnk = 1:length(pn_key)
for m = 1:length(vb)
if load_sequence
load(['C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\MPI_April\',filename,'.mat'],'X');
spectrum_plot(X.signal',X.fs,'spectrum');
else
% 1) PRBS Generation
O = 17; %order of prbs
O = 18; %order of prbs
N = 2^(O-1); %length of prbs
[~,seed] = prbs(O,1); %initialize first seed of prbs
bitpattern=[];
for i = 1:log2(M)
[bitpattern(:,i),seed] = prbs(O,N,seed);
end
@@ -62,12 +44,10 @@ for pnk = 1:length(pn_key)
digimod_out = PAMmapper(M,0).map(bits);
digimod_out.fs = fsym;
X = Pulseformer("fsym",fsym,"fdac",fdac,"pulse","rrc","pulselength",16,"rrcalpha",0.01).process(digimod_out);
X = Pulseformer("fsym",fsym,"fdac",fdac,"pulse","rrc","pulselength",16,"rrcalpha",0.1).process(digimod_out);
% 5) AWG (lowpass, quantization, sample and hold)
%X = M8196A().process(X);
kover = 16;
X = AWG("fdac",fdac,"dac_min",-1,"dac_max",1,"H_lpf",LP_awg,"kover",kover).process(X);
X = AWG("fdac",fdac,"dac_min",-1,"dac_max",1,"H_lpf",LP_awg,"kover",kover,"bit_resolution",5,"lpf_active",1).process(X);
% 6) Lowpass behavior before laser
X = LP_laser.process(X);
@@ -75,14 +55,36 @@ for pnk = 1:length(pn_key)
% 7) Normalize signal
X = X.normalize("mode","oneone");
%save(['C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\MPI_April\',char(filename)],'X');
end
sir = [20:2:36]; %decibel = attenuation of interference path
laser_linewidth = [1e5 1e6 3e6 10e6];
pn_key = [1:10];
vp = [0.25,0.5,0.75,1];
vb = [1:0.1:1.8];
rop = -9:3;
% sir = 25;
% laser_linewidth = 1e6;
% pn_key = 1;
% vp = 0.8;
% vb = 1;
cnt = 1;
for s = 1:length(sir)
for l = 1:length(laser_linewidth)
for pnk = 1:length(pn_key)
for n = 1:length(vp)
for m = 1:length(vb)
cnt = cnt+1;
% 1) Laser; Modulation -> OPTICAL DOMAIN
u_pi = 2;
vbias = -vb(m)*u_pi;
extmodlaser = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",X.fs,"lambda",1290,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",pn_key(pnk));
vbias = -vb(m);
extmodlaser = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",X.fs,"lambda",1290,"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth(l),"randomkey",pn_key(pnk));
E = X.*vp(1);
% E.signal = min(max(E.signal,-0.2),0.2);
[Opt,extmodlaser] = extmodlaser.process(E);
% figure(m)
@@ -91,33 +93,37 @@ for pnk = 1:length(pn_key)
% xlabel('Input in V')
% ylabel('abs(Output) in mW')
% ER = 10*log10(max(abs(Opt.signal).^2)/min(abs(Opt.signal).^2));
Opt = LP_opt.process(Opt);
cspr(m) = Opt.cspr;
cspr(s,l,pnk,n,m) = Opt.cspr;
mod_out_pow(s,l,pnk,n,m) = Opt.power;
% 2) ping pong fiber propagation
Interference_sig = Fiber("fsimu",Opt.fs,"fiber_length",mpi_path*2/1000,"alpha",0,"D",0,"lambda0",1310,"gamma",0).process(Opt);
Interference_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",-sir).process(Interference_sig);
Interference_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",-sir(s)).process(Interference_sig);
% In the meantime: delay the main signal
[Main_sig,n] = Opt.delay("delay_meter",mpi_path*2);
[Main_sig,dly] = Opt.delay("delay_meter",mpi_path*2);
% Add
Combined_sig = Main_sig + Interference_sig;
% Cut (due to the delays there is a jump in the signals)
if n == 0;n = 1;end
Combined_sig.signal = Combined_sig.signal(ceil(n):end);
if dly == 0;dly = 1;end
Combined_sig.signal = Combined_sig.signal(ceil(dly):end);
% Fiber
Combined_sig = Fiber("fsimu",Combined_sig.fs,"fiber_length",0,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.08).process(Combined_sig);
Combined_sig = Fiber("fsimu",Combined_sig.fs,"fiber_length",2,"alpha",0.3,"D",0,"lambda0",1310,"gamma",0,"Dslope",0.08).process(Combined_sig);
for i = 1:length(rop)
parfor i = 1:length(rop)
% Set ROP
Rx_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",rop(i)).process(Combined_sig);
rop_save(m,i) = Rx_sig.power;
rop_save(s,l,pnk,n,m,i) = Rx_sig.power;
% Square Law
Rx_sig = Photodiode("fsimu",Rx_sig.fs,"dark_current",2e-08,"responsivity",1,"temperature",20).process(Rx_sig);
@@ -137,9 +143,30 @@ for pnk = 1:length(pn_key)
% Sync Rx signal with reference
[Rx_sig,D,cuts] = Rx_sig.tsynch("reference",digimod_out,"fs_ref",fsym);
% % simple EQ (optimum mudc: 0.05 -> 0.005)
EQ_sig = EQ_silas_plain("Ne",[20,8,8],"Nb",[2,0,0],"trainlength",4096,"mu_dc_dd",0.005,"mu_dc_train",0.05,...
"mu_ffe_train",0.005,"mu_combined_dd",[0.0004 0.0006 0.0003 0.005],"ddloops",3,'trainloops',3,'sps',2).process(Rx_sig,digimod_out);
% % % simple EQ (optimum mudc: 0.05 -> 0.005)
% EQ_sig = EQ_silas_plain("Ne",[20,8,8],"Nb",[2,0,0],"trainlength",4096,"mu_dc_dd",0.005,"mu_dc_train",0.05,...
% "mu_ffe_train",0.005,"mu_combined_dd",[0.0004 0.0006 0.0003 0.005],"ddloops",3,'trainloops',3,'sps',2).process(Rx_sig,digimod_out);
%
% EQ_sig = EQ("K",2,"plottrain",0,"plotfinal",0,...
% "training_length",4096,"training_loops",3,...
% "Ne",[20,8,8],"Nb",[2,0,0],...
% "DCmu",0.005,"DDmu",[0.0004 0.0006 0.0003 0.005],"DFEmu",0.005,"FFEmu",0.00,...
% "dd_loops",3,"epsilon",[10 100 1000 ],"M",2,...
% "thres",[0.005 0.004 0.0005 ],"l1act",0,"delay",0,"rho",0.0005,"ideal_dfe",0,"DB_aim",0).process(Rx_sig,digimod_out);
EQ_sig = EQ_silas("Ne",[20,2,0],"Nb",[2,0,0],"trainlength",4096,...
"sps",2,...
"mu_dc_dd",0.00,...
"mu_dc_train",0.00,...
"mu_ffe_train",0.00,...
"mu_dfe_train",0.005,...
"mu_ffe_dd",[0.0004 0.0006 0.0003],...
"mu_dfe_dd",0.005,...
"ddloops",3,...
"trainloops",3,...
"eq_parallelization_blocklength",1, ...
"eq_updatelatency",1,...
"eq_avg_blocklength",0).process(Rx_sig,digimod_out);
% Demap
Rx_Bits = PAMmapper(M,0).demap(EQ_sig);
@@ -147,52 +174,65 @@ for pnk = 1:length(pn_key)
Rx_symboldecision = PAMmapper(M,0).decide_pamlevel(EQ_sig,"symbol_levels",unique(digimod_out.signal));
levels = PAMmapper(M,0).separate_pamlevels(EQ_sig);
level_avg(:,m,i) = mean(levels,'omitnan');
level_std(:,m,i) = std(levels,'omitnan');
%levels = PAMmapper(M,0).separate_pamlevels(Rx_sig.resample("fs_in",Rx_sig.fs,"fs_out",fsym));
level_avg(s,l,pnk,n,m,i,:) = mean(levels,'omitnan');
level_std(s,l,pnk,n,m,i,:) = std(levels,'omitnan');
% BER
[~,errors_bm,BER(m,i),errors] = calc_ber(Rx_Bits.signal,bitpattern,"skip_front",0,"skip_end",0,"returnErrorLocation",1);
[~,errors_bm,BER(s,l,pnk,n,m,i),errors] = calc_ber(Rx_Bits.signal,bitpattern,"skip_front",0,"skip_end",0,"returnErrorLocation",1);
formatted_ber = sprintf('%.1e', BER(m,i));
disp(formatted_ber);
formatted_ber = sprintf('%.1e', BER(s,l,pnk,n,m,i));
disp(['SIR: ',num2str(sir(s)),'; Lw:',num2str(laser_linewidth(l)),'; Key:',num2str(pn_key(pnk)),'; Vpeak: ',num2str(vp(n)),'; Vbias',num2str(vbias),'; BER: ',formatted_ber,'; run: ',num2str(cnt),' / 12961']);
% plot_analysis_window;
% drawnow;
end
end
end
plot_analysis_window;
save(['C:\Users\Silas\Nextcloud4\Dokumente\02_Ablage_Office\MPI\Investigation_April_2024\','PAM_',num2str(M),'_mpi_',num2str(mpi_path),'_lw_',num2str(laser_linewidth)],"BER");
% BER plot
figure(340)
cols = linspecer(7);
for m = 1:size(BER,1)
hold on
plot(rop,BER(m,:),'DisplayName',['Bias: ',num2str(vb(m)), ' V'],'LineStyle','-','Color',cols(m,:),'LineWidth',1,'Marker','o','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',cols(m,:));
save('big_run_easy_EQ_one_nonlin');
disp('saved_run2');
end
end
end
set(gca,'YScale','log');
legend
xlabel("ROP in dBm")
yline(3.8e-3,'DisplayName','FEC');
figure(21)
hold on
plot(rop,mean(BER),'DisplayName',['Modulation: ',num2str(2*vp/extmodlaser.u_pi*100), ' $\%$'],'LineStyle','-','Color',cols(2,:),'LineWidth',1);
set(gca,'YScale','log');
legend
ylabel("ROP in dBm")
yline(3.8e-3,'DisplayName','FEC');
%check Rx and TX symbols
figure(101)
scatter(1:100,Rx_symboldecision.signal(1:100),10,'o');
hold on
scatter(1:100,digimod_out.signal(1:100),5,'x');
% save(['C:\Users\Silas\Nextcloud4\Dokumente\02_Ablage_Office\MPI\Investigation_April_2024\','PAM_',num2str(M),'_mpi_',num2str(mpi_path),'_lw_',num2str(laser_linewidth)],"BER");
%
% % BER plot
% figure(340)
% cols = linspecer(7);
% for m = 1:size(BER,1)
% hold on
% plot(rop,BER(m,:),'DisplayName',['Bias: ',num2str(vb(m)), ' V'],'LineStyle','-','Color',cols(m,:),'LineWidth',1,'Marker','o','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',cols(m,:));
%
% end
% set(gca,'YScale','log');
% legend
% xlabel("ROP in dBm")
% yline(3.8e-3,'DisplayName','FEC');
%
%
% figure(21)
% hold on
% plot(rop,mean(BER),'DisplayName',['Modulation: ',num2str(2*vp/extmodlaser.u_pi*100), ' $\%$'],'LineStyle','-','Color',cols(2,:),'LineWidth',1);
% set(gca,'YScale','log');
% legend
% ylabel("ROP in dBm")
% yline(3.8e-3,'DisplayName','FEC');
%
%
%
%
%
%
%
%
% %check Rx and TX symbols
% figure(101)
% scatter(1:100,Rx_symboldecision.signal(1:100),10,'o');
% hold on
% scatter(1:100,digimod_out.signal(1:100),5,'x');

9
projects/MPI_April/mzm_er.m Normal file
View File

@@ -0,0 +1,9 @@
field=sqrt(10^(3/10-3)); %dbm to sqrt(mw)
vpi = 2;
vbias = 1;
vin = 0.1;
(field * cos(pi/2*(vin+vbias)/vpi)).^2

8
projects/MPI_April/plot_analysis_window.m
View File

@@ -16,9 +16,9 @@ ylim([-100,0]);
%Phase Investigation
subplot(3,2,3)
hold on
phase_int = extmodlaser.phase(n:end);
phase_main = delayseq(extmodlaser.phase,n);
phase_main = phase_main(n:end);
phase_int = extmodlaser.phase(ceil(n):end);
phase_main = delayseq(extmodlaser.phase,ceil(n));
phase_main = phase_main(ceil(n):end);
phase_diff = phase_int - phase_main;
t = (1:length(phase_int))' ./ extmodlaser.fsimu ;
plot(t*1e6,phase_int,'Color',colpairs(1,:),'DisplayName','Interferer Phase');
@@ -53,7 +53,7 @@ for h = 1:size(levels,2)
scatter(t*1e6,levels(:,h),1,'.');
hold on
end
yline(PAMmapper(M,0).thresholds);
%yline(PAMmapper(M,0).thresholds);
title(['BER: ',sprintf('%.1e', BER(m,i))]);
%Histogram of EQzed Signal

61
projects/MPI_April/save_to_warehouse.m Normal file
View File

@@ -0,0 +1,61 @@
sir = [20:2:36]; %decibel = attenuation of interference path
laser_linewidth = [1e5 1e6 3e6 10e6];
pn_key = [1:10];
vp = [0.25];
vb = [1:0.1:1.8];
rop = -9:3;
params = struct;
params.sir = [20:2:36]; %decibel = attenuation of interference path
params.laser_linewidth = [1e5 1e6 3e6 10e6];
params.pn_key = [1:10];
params.vp = [0.25,0.5,0.75,1];
params.vb = [1:0.1:1.8];
params.rop = -9:3;
wh = DataStorage(params);
wh.addStorage("ber");
wh.addStorage("level_avg");
wh.addStorage("level_std");
wh.addStorage("rop_save");
wh.addStorage("cspr");
wh.addStorage("mod_out_pow");
cnt = 1;
for s = 1:length(sir)
for l = 1:length(laser_linewidth)
for pnk = 1:length(pn_key)
for n = 1
for m = 1:length(vb)
for i = 1:length(rop)
cnt = cnt +1;
wh.addValueToStorage(BER(s,l,pnk,n,m,i),'ber',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
wh.addValueToStorage(level_avg(s,l,pnk,n,m,i,:),'level_avg',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
wh.addValueToStorage(level_std(s,l,pnk,n,m,i,:),'level_std',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
wh.addValueToStorage(rop_save(s,l,pnk,n,m,i),'rop_save',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
wh.addValueToStorage(cspr(s,l,pnk,n,m),'cspr',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
wh.addValueToStorage(mod_out_pow(s,l,pnk,n,m),'mod_out_pow',sir(s),laser_linewidth(l),pn_key(pnk),vp(n),vb(m),rop(i));
end
end
end
end
end
end
% 4) Hey! the warehouse is here and (hopefully) filled with data :-)
% Create a save dialog
defaultDir = 'C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\MPI_April';
defaultExt = '*.mat';
[filename, pathname] = uiputfile(fullfile(defaultDir, defaultExt),'', 'wh.mat');
% Check if the user pressed Cancel
if isequal(filename, 0) || isequal(pathname, 0)
disp('Save operation canceled.');
else
% Save the variable to the selected file
save(fullfile(pathname, filename), 'wh');
disp(['Variable "wh" saved to: ', fullfile(pathname, filename)]);
end