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- Correction of the weighted DFE function in EQ.m
- Some evaluation scripts for FSO Data
This commit is contained in:
magf
2026-02-09 13:04:20 +01:00
parent 58e72070d9
commit 3edd64d365
22 changed files with 759 additions and 186 deletions
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4
Classes/00_signals/Signal.m
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@@ -172,9 +172,9 @@ classdef Signal
hold on; hold on;
if isempty(options.color) if isempty(options.color)
plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', '.', 'LineStyle','none', 'MarkerSize', 0.1); plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', 'none', 'LineStyle','-', 'MarkerSize', 0.1);
else else
plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', '.', 'LineStyle','none', 'MarkerSize', 0.1,'Color',options.color); plot(t* 1e6, sig(1:length(t)), 'DisplayName', dn, 'LineWidth', 0.1, 'Marker', 'none', 'LineStyle','-', 'MarkerSize', 0.1,'Color',options.color);
end end
% 2 c) % 2 c)
% - xlabel if not already here: time in readable format (1 ms and not 1e-3 s) % - xlabel if not already here: time in readable format (1 ms and not 1e-3 s)

154
Classes/04_DSP/Equalizer/EQ.m
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@@ -10,10 +10,12 @@ classdef EQ < handle
training_length %Number of training symbols training_length %Number of training symbols
training_loops %Number of loops through sequence for training mode training_loops %Number of loops through sequence for training mode
ideal_dfe %Error free DFE decisions ideal_dfe %Error free DFE decisions
weighted_DFE %Weighted DFE on/off weighted_DFE %Weighted DFE off (0)/on (1)/PDFE (2)
weighted_DFE_mode %Weighted DFE mode weighted_DFE_mode %Weighted DFE mode
weighted_DFE_d_min %d_min threshold parameter for weighted DFE mode 1 weighted_DFE_d_min %d_min threshold parameter for weighted DFE mode 1
weighted_DFE_I_mode %[a_s, b_s, I_max]-parameters for the weighted DFE weighted_DFE_I_mode %[a_s, b_s, I_max]-parameters for the weighted DFE
PDFE_coefficient %Coefficient for PDFE
weighted_error %error based on hard- or weighted decision
DB_aim %Aim at duobinary output sequence DB_aim %Aim at duobinary output sequence
@@ -43,7 +45,6 @@ classdef EQ < handle
save_taps save_taps
%during simulation %during simulation
k0 k0
b b
@@ -76,6 +77,8 @@ classdef EQ < handle
options.weighted_DFE_mode = 'R1'; options.weighted_DFE_mode = 'R1';
options.weighted_DFE_d_min = 0.5; options.weighted_DFE_d_min = 0.5;
options.weighted_DFE_I_mode = [5,0.5,0.6]; options.weighted_DFE_I_mode = [5,0.5,0.6];
options.PDFE_coefficient = 0.5;
options.weighted_error = 0; %0: Error based on hard-decision. 1: Error based on weighted decision.
options.DB_aim %Aim at duobinary output sequence options.DB_aim %Aim at duobinary output sequence
@@ -243,19 +246,11 @@ classdef EQ < handle
cnt = 1; cnt = 1;
m = obj.k0+1; % starting symbol index at the delay compared to the training sequence m = obj.k0+1; % starting symbol index at the delay compared to the training sequence
% n => index in rx data sequence
%Step From: Oversampling(=2) * Startdelay + 1
%Step Width: Oversampling(=2)
%Step To: Oversampling(=2) * Training Length
for n = obj.K*obj.k0+1:obj.K:obj.K*obj.training_length for n = obj.K*obj.k0+1:obj.K:obj.K*obj.training_length
% m => index in reference sequence % m => index in reference sequence
m = m+1; m = m+1;
%
%dc_ = mean(data(obj.Ne(1)+n+(obj.K-1):-1:n+obj.K).');
% cut symbols from rx data sequence % cut symbols from rx data sequence
X_1 = data(obj.Ne(1)+n+(obj.K-1):-1:n+obj.K).'; X_1 = data(obj.Ne(1)+n+(obj.K-1):-1:n+obj.K).';
@@ -275,8 +270,6 @@ classdef EQ < handle
error = e_dc + e_ffe - e_dfe - ref_in(m-obj.k0); error = e_dc + e_ffe - e_dfe - ref_in(m-obj.k0);
%error = e_dc + e_.'*input_vec - b_.'*reference_vec - ref_in(m-obj.k0);
if real(obj.FFEmu) if real(obj.FFEmu)
if obj.l1act if obj.l1act
sgn_e = e_; sgn_e = e_;
@@ -297,28 +290,13 @@ classdef EQ < handle
e_dc = e_dc - obj.DCmu*error; e_dc = e_dc - obj.DCmu*error;
% obj.error_log.e_ffe(cnt,trainloops) = e_ffe;
% obj.error_log.e_dfe(cnt,trainloops) = e_dfe;
% obj.error_log.e_(cnt,trainloops) = error;
cnt = cnt+1; cnt = cnt+1;
if obj.Nb(1) > 0 if obj.Nb(1) > 0
b_ = b_ + obj.DFEmu*error*reference_vec; % Seems like normalized DFE has worse performance b_ = b_ + obj.DFEmu*error*reference_vec; % Seems like normalized DFE has worse performance
end end
% figure(111);stem((e_),'Markersize',2);ylim([-1 1]);title('FFE Filter Taps');
%
% figure(222);
% stem(input_vec);ylim([-3 3]);
% hold on;
% stem(reference_vec);ylim([-3 3]);
% yline(error,'LineWidth',2); title('Input Vector');
% hold off
end end
end end
%% %%
% Plot the intermediate coefficients after training mode % Plot the intermediate coefficients after training mode
obj.b = b_(1:obj.Nb(1)); obj.b = b_(1:obj.Nb(1));
@@ -349,10 +327,8 @@ classdef EQ < handle
subplot(2,3,6);stem(obj.b3,'Markersize',2); subplot(2,3,6);stem(obj.b3,'Markersize',2);
title('DFE coeff nl 3rd') title('DFE coeff nl 3rd')
xlabel('coefficient index'); ylabel('value'); set(gca,'Fontsize',12) xlabel('coefficient index'); ylabel('value'); set(gca,'Fontsize',12)
%set(gcf,'Position',[200 500 700 400])
end end
if obj.l1act if obj.l1act
neg_lin = find(abs(obj.e) < obj.thres(1)); neg_lin = find(abs(obj.e) < obj.thres(1));
neg_2nd = find(abs(obj.e2) < obj.thres(2)); neg_2nd = find(abs(obj.e2) < obj.thres(2));
@@ -401,6 +377,7 @@ classdef EQ < handle
cnt = 1; cnt = 1;
m = 0; m = 0;
output_vec = zeros(1,floor(length(data_in)/obj.K)); % initilaization of the output vector output_vec = zeros(1,floor(length(data_in)/obj.K)); % initilaization of the output vector
output_vec_weighted = zeros(size(output_vec));
dd_DFE = zeros(obj.Nb(1),1); dd_DFE = zeros(obj.Nb(1),1);
D_2 = zeros(Nb2,1); D_2 = zeros(Nb2,1);
D_3 = zeros(Nb3,1); D_3 = zeros(Nb3,1);
@@ -418,7 +395,6 @@ classdef EQ < handle
if obj.load_decisions if obj.load_decisions
pathn = evalin('base','modeldir'); pathn = evalin('base','modeldir');
temp = load([pathn, 'MLSE_out', '.mat']) ; temp = load([pathn, 'MLSE_out', '.mat']) ;
%eval(['dd_out_vals = temp.', 'a', ';']) ;
dd_out_vals=temp.a; dd_out_vals=temp.a;
dd_out = zeros(size(data_in)); dd_out = zeros(size(data_in));
dd_out(1:2:length(data_in)) = dd_out_vals; dd_out(1:2:length(data_in)) = dd_out_vals;
@@ -440,79 +416,103 @@ classdef EQ < handle
end end
output_vec(m) = e_dc + input_vec.'*coeff; output_vec(m) = e_dc + input_vec.'*coeff;
y_raw = output_vec(m); % ungeweighteter Equalizer-Ausgang
if ~obj.load_decisions if ~obj.load_decisions
[~,dd_idx] = min(abs(output_vec(m) - constellation_in_)); % decision for closest constellation point [~,dd_idx] = min(abs(output_vec(m) - constellation_in_)); % decision for closest constellation point
dd_out(k) = constellation_in_(dd_idx); dd_out(k) = constellation_in_(dd_idx);
end end
% Implementation of a weighted DFE in % ---------- WDFE / PDFE ----------
% order to prevent error propagation. fb_sym = dd_out(k);
% For further details, study [1], chapter 3.2.2 -
% Modifications of DFE
if obj.weighted_DFE if obj.weighted_DFE ~= 0
% define new constellations % Get constellation
const = unique(ref_in); const = obj.constellation_in;
% determine reliability factor gamma_k % Half minimum symbol distance (for normalization of |x - xhat|)
const_s = sort(const(:).');
d = diff(const_s);
dmin = min(d(d>0));
halfStep = dmin/2;
% Reliability gamma_k
if output_vec(m) > min(const) && output_vec(m) < max(const) if output_vec(m) > min(const) && output_vec(m) < max(const)
gamma_k = 1 - abs(output_vec(m) - dd_out(k)); gamma_k = 1 - abs(output_vec(m) - dd_out(k))/halfStep;
gamma_k = max(0, min(1, gamma_k)); % clamp to [0,1]
else else
gamma_k = 1; gamma_k = 1;
end end
% select mode % f(gamma_k)
if strcmp(obj.weighted_DFE_mode,'R1') if obj.weighted_DFE == 1
if gamma_k >= obj.weighted_DFE_d_min switch obj.weighted_DFE_mode
f_gamma_k = 1; case 'R1'
else f_gamma_k = double(gamma_k >= obj.weighted_DFE_d_min);
f_gamma_k = 0;
end case 'R2'
elseif strcmp(obj.weighted_DFE_mode,'R2')
f_gamma_k = gamma_k; f_gamma_k = gamma_k;
elseif strcmp(obj.weighted_DFE_mode,'I1')
nom = 1-exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1)); case 'I1'
denom = 1+exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1)); a_s = obj.weighted_DFE_I_mode(1);
f_gamma_k = (1/2)*((nom/denom) - 1); b_s = obj.weighted_DFE_I_mode(2);
elseif strcmp(obj.weighted_DFE_mode,'I2') t = a_s*((gamma_k/b_s) - 1);
nom = 1-exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1)); f_gamma_k = 0.5*(tanh(t) + 1);
denom = 1+exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
f_gamma_k = (obj.weighted_DFE_I_mode(3)/2)*((nom/denom) - 1); case 'I2'
a_s = obj.weighted_DFE_I_mode(1);
b_s = obj.weighted_DFE_I_mode(2);
Imax = obj.weighted_DFE_I_mode(3);
t = a_s*((gamma_k/b_s) - 1);
f_gamma_k = (Imax/2)*(tanh(t) + 1);
otherwise
error('Unknown weighted_DFE_mode');
end end
% calculate weighted output
output_vec(m) = f_gamma_k.*dd_out(k)+(1-f_gamma_k).*output_vec(m); % Weighted decision
xbar = f_gamma_k*dd_out(k) + (1 - f_gamma_k)*output_vec(m);
elseif obj.weighted_DFE == 2
% PDFE
xbar = obj.PDFE_coefficient*dd_out(k) + (1 - obj.PDFE_coefficient)*output_vec(m);
end
output_vec_weighted(m) = xbar;
fb_sym = xbar;
output_vec(m) = xbar;
end end
if obj.Nb(1) > 0 if obj.Nb(1) > 0
dd_DFE(2:end) = dd_DFE(1:end-1); dd_DFE(2:end) = dd_DFE(1:end-1);
dd_DFE(1) = dd_out(k); dd_DFE(1) = fb_sym;
if obj.ideal_dfe && m > obj.k0 if obj.ideal_dfe && m > obj.k0
dd_DFE(1) = ref_in(m-obj.k0); dd_DFE(1) = ref_in(m-obj.k0);
end end
[D_2,D_3] = obj.calc_nl_vecs(dd_DFE,ind_mat_DFE_2nd,ind_mat_DFE_3rd,norm_fac_DFE2,norm_fac_DFE3,delta_DFE2,delta_DFE3,cplx);
[D_2,D_3] = obj.calc_nl_vecs(dd_DFE,ind_mat_DFE_2nd,ind_mat_DFE_3rd,...
norm_fac_DFE2,norm_fac_DFE3,delta_DFE2,delta_DFE3,cplx);
end
if obj.weighted_DFE ~= 0 && obj.weighted_error
% Error weighted decision
error = y_raw - output_vec(m);
else
% Error hard decision
error = y_raw - dd_out(k);
end end
% if dd_loop ~= 21
error = output_vec(m) - dd_out(k);
% else
% error = 0;
% end
coeff = coeff - mu_mat*error*conj(input_vec); coeff = coeff - mu_mat*error*conj(input_vec);
% e_save(:,save_ind) = coeff;
% save_ind = save_ind+1;
if 1 % mu_mat ~= 0 if 1 % mu_mat ~= 0
e_dc = e_dc - obj.DCmu*error; e_dc = e_dc - obj.DCmu*error;
% error_log(cnt,dd_loop) = e_dc;
cnt = cnt+1; cnt = cnt+1;
end end
end end
end end
%figure(2023);plot(error_log(:,1))
% shifting the output sequence by k0 symbols % shifting the output sequence by k0 symbols
yout = (circshift(output_vec.',-(obj.k0))).'; %(circshift(dd_out.',-(obj.k0))).'; yout = (circshift(output_vec.',-(obj.k0))).'; %(circshift(dd_out.',-(obj.k0))).';
@@ -581,12 +581,6 @@ classdef EQ < handle
% save frequency response to the work space % save frequency response to the work space
if obj.save_taps if obj.save_taps
% save the FFE coefficients to the work space
% pathn = evalin('base','modeldir');
% eval([obj.field_ffe, ' = obj.e ;']) ;
% eval([obj.field_dfe, ' = b ;']) ;
% eval(['save(''', pathn, '\',obj.filen,''', ''', obj.field_ffe,''', ''',obj.field_dfe,''') ;']) ;
save("coefficients",obj.e, obj.b); save("coefficients",obj.e, obj.b);
end end
@@ -726,19 +720,11 @@ classdef EQ < handle
ind_mat_3rd2 = NaN(N3,3); ind_mat_3rd2 = NaN(N3,3);
count = 1; count = 1;
% for t = 1:Ne3
% ind_mat_3rd2(count,:) = [t t t];
% count = count + 1;
% end
for t = 1:Ne3 for t = 1:Ne3
% ind_mat_3rd2(count,:) = [t t t];
% count = count + 1;
for u = t:min(Ne3,t+len_3rd) for u = t:min(Ne3,t+len_3rd)
for v = unique([t u]) for v = unique([t u])
ind_mat_3rd2(count,:) = [t v u]; ind_mat_3rd2(count,:) = [t v u];
count = count + 1; count = count + 1;
% ind_mat_3rd2(count,:) = [t u u];
% count = count + 1;
end end
end end
end end
@@ -785,5 +771,5 @@ classdef EQ < handle
end end
% References % References
% [1] T. J. Wettlin, “Experimental Evaluation of Advanced Digital Signal Processing for Intra-Datacenter Systems using Direct-Detection,” 2023. [Online]. Available: https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2023-00703-8 % [1] T. J. Wettlin, “Experimental Evaluation of Advanced Digital Signal Processing for Intra-Datacenter Systems using Direct-Detection,” 2023.
% [Online]. Available: https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2023-00703-8

3
Classes/04_DSP/Equalizer/ML_MLSE.m
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@@ -621,7 +621,8 @@ classdef ML_MLSE < handle
% --- Initialize weights % --- Initialize weights
if isempty(obj.w) || any(size(obj.w) ~= [obj.Nf+1,obj.nFeasible]) if isempty(obj.w) || any(size(obj.w) ~= [obj.Nf+1,obj.nFeasible])
obj.w = randn(obj.Nf+1,obj.nFeasible); % obj.w = randn(obj.Nf+1,obj.nFeasible);
obj.w = zeros(obj.Nf+1,obj.nFeasible);
end end
% --- Fast lookup tables % --- Fast lookup tables

3
Classes/04_DSP/Timing_Recovery.m
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@@ -1,6 +1,7 @@
classdef Timing_Recovery < handle classdef Timing_Recovery < handle
properties(Access=public) properties(Access=public)
modulation
timing_error_detector timing_error_detector
sps sps
damping_factor damping_factor
@@ -12,6 +13,7 @@ classdef Timing_Recovery < handle
function obj = Timing_Recovery(options) function obj = Timing_Recovery(options)
arguments(Input) arguments(Input)
options.modulation = 'PAM/PSK/QAM'
options.timing_error_detector = 'Gardner'; options.timing_error_detector = 'Gardner';
options.sps = 2; options.sps = 2;
options.damping_factor = 1.0; options.damping_factor = 1.0;
@@ -32,6 +34,7 @@ classdef Timing_Recovery < handle
function [data_out,timing_error] = process(obj, data_in) function [data_out,timing_error] = process(obj, data_in)
timing_synchronization = comm.SymbolSynchronizer( ... timing_synchronization = comm.SymbolSynchronizer( ...
"Modulation", obj.modulation, ...
"TimingErrorDetector", obj.timing_error_detector, ... "TimingErrorDetector", obj.timing_error_detector, ...
"SamplesPerSymbol", obj.sps, ... "SamplesPerSymbol", obj.sps, ...
"DampingFactor", obj.damping_factor, ... "DampingFactor", obj.damping_factor, ...

4
Functions/EQ_structures/ml_mlse.m
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@@ -101,11 +101,11 @@ switch precode_mode
tx_bits_precoded = mapper.demap(tx_symbols_precoded); tx_bits_precoded = mapper.demap(tx_symbols_precoded);
rx_bits = mapper.demap(eq_signal_hd_precoded); rx_bits = mapper.demap(eq_signal_hd_precoded);
[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1); [~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 150, "skip_end", 150, "returnErrorLocation", 1);
% B) Just determine BER % B) Just determine BER
rx_bits = mapper.demap(eq_signal_hd); rx_bits = mapper.demap(eq_signal_hd);
[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 30000, "skip_end", 150, "returnErrorLocation", 1); [bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 150, "skip_end", 150, "returnErrorLocation", 1);
case db_mode.db_precoded case db_mode.db_precoded
% Data is precoded on TX side % Data is precoded on TX side

35
projects/FSO_transmission/Evaluation Scripts/Optimize_WDFE_Parameters.m Normal file
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@@ -0,0 +1,35 @@
%%
current = 225:10:285;
current = string(current);
power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power);
num_pf_coeff = 4;
taps_ffe = [300, 0, 0];
taps_dfe = [2, 0, 0];
M = 4;
trlength = 4096*4;
x = 225:10:285;
BER_PAM_4 = [];
filter_length = 210;
eq_method = 2;
num_signal_sweep = 11;
our_signal = 1;
idx = 4;
obj = @(x) first_analysis_ber( ...
current(idx), power(idx), num_pf_coeff, taps_ffe, taps_dfe, ...
M, trlength, eq_method, filter_length, num_signal_sweep, our_signal, x);
x0 = [1 0.1 0.1];
lb = [1 0 0];
ub = [10 1 1];
opts = optimoptions('fmincon', ...
'Display','iter', ...
'Algorithm','sqp', ...
'MaxFunctionEvaluations', 500, ...
'StepTolerance', 1e-3, ...
'OptimalityTolerance', 1e-3);
[xbest, berbest] = fmincon(obj, x0, [], [], [], [], lb, ub, [], opts);

38
projects/FSO_transmission/Evaluation Scripts/evalscript_cell.m Normal file
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@@ -0,0 +1,38 @@
%%
current = 225:10:285;
current = string(current);
power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power);
curr_pow_num = 4;
num_pf_coeff = 4;
taps_ffe = [300, 0, 0];
taps_dfe = [0, 0, 0];
M = 4;
trlength = 4096*4;
eq_method = 2;
filter_length = 210;
our_signal = 0;
BER_vec = [];
for i = 1:15
BER_value = first_analysis_ber(current(curr_pow_num), power(curr_pow_num), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, i, our_signal);
BER_vec = [BER_vec, BER_value];
end
%%
BER_Our_Signal = [1.2e-3,1.3e-3,9.0e-4,3.8e-4,4.8e-4,4.8e-4,5.7e-4,4.1e-4,4.8e-4,5.6e-4,3.8e-4,4.1e-4,4.1e-4,5.2e-4,3.8e-4];
BER_Their_Signal = [5.7e-4,4.0e-4,5.2e-4,4.9e-4,5.2e-4,5.5e-4,4.8e-4,4.0e-4,3.6e-4,4.6e-4,5.7e-4,5.3e-4,4.5e-4,5.9e-4,6.4e-4];
figure;
x = 1:15;
plot(x, BER_Our_Signal, 'Marker', 'o', 'LineWidth', 1.75)
hold on
plot(x, BER_Their_Signal, 'Marker', 'o', 'LineWidth', 1.75)
title('BER for FFE+PF+VNLE', 'Interpreter', 'latex')
xlabel('Cell Entry', 'Interpreter', 'latex')
ylabel('BER', 'Interpreter', 'latex')
legend('Our Signal', 'Their Signal', 'Interpreter', 'latex')
grid('minor')
xlim([0 16])
ylim([3e-4, 1.5e-3])
hold off

20
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_2.m
View File

@@ -11,24 +11,28 @@ trlength = 4096*2;
x = 225:10:285; x = 225:10:285;
BER_PAM_2 = []; BER_PAM_2 = [];
post_only = 0; post_only = 0;
filter_length_vec = 140;
num_signal = 11;
our_signal = 1;
for eq_method = 2:4 for eq_method = 1:4
if ~post_only if ~post_only
for j = 1:length(current) for j = 1:length(current)
BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method); BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length_vec, num_signal, our_signal);
BER_PAM_2 = [BER_PAM_2, BER_run]; BER_PAM_2 = [BER_PAM_2, BER_run];
end end
save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_2_' + string(eq_method) + '.mat', 'x', 'BER_PAM_2')
end end
save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_' + string(eq_method) + '.mat', 'x', 'BER_PAM_2')
BER_PAM_2 = [];
end end
%% %%
x = 225:10:285; x = 225:10:285;
for k = 1:4 for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_2_' + string(k) + '.mat'); BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_' + string(k) + '.mat');
BER = BER.BER_PAM_2; BER = BER.BER_PAM_2;
figure(202120) figure(202120)
@@ -50,10 +54,10 @@ legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Location','southwest', 'FontSize', 14) 'Location','southwest', 'FontSize', 14)
% FEC Labels direkt im Plot % FEC Labels direkt im Plot
text(280,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex') text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(280,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex') text(221,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(280,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex') text(221,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(280,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex') text(231,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex') xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
ylabel('BER', 'Interpreter','latex') ylabel('BER', 'Interpreter','latex')

74
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_2_opt.m Normal file
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@@ -0,0 +1,74 @@
%%
current = 225:10:285;
current = string(current);
power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power);
num_pf_coeff = 4;
taps_ffe = [200, 0, 0];
taps_dfe = [0, 0, 0];
M = 2;
trlength = 4096*2;
x = 225:10:285;
BER_PAM_2 = [];
BER_num_signal_sweep = [];
BER_num_signal_sweep_matrix = [];
post_only = 0;
filter_length = 140;
our_signal = 1;
idx_opt = [];
for eq_method = 1:4
for j = 1:length(power)
for num_signal_sweep = 1:15
BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal_sweep, our_signal);
BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
end
[BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
BER_PAM_2 = [BER_PAM_2, BER_opt];
idx_opt = [idx_opt, num_signal_opt];
BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
BER_num_signal_sweep = [];
end
save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(eq_method) + '.mat', 'BER_PAM_2', 'BER_num_signal_sweep_matrix', 'idx_opt')
BER_PAM_2 = [];
idx_opt = [];
end
%%
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(k) + '.mat');
BER_values = BER.BER_PAM_2;
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
old_BER = [-1.5, -1.75, -2, -2.3, -2.6, -2.25, -1.95];
old_BER = 10.^(old_BER);
plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ...
'Location','northwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
% title('BER for PAM-4', 'Interpreter','latex')
grid minor
ylim([1e-4 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

39
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4.m
View File

@@ -5,34 +5,37 @@ power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power); power = string(power);
num_pf_coeff = 4; num_pf_coeff = 4;
taps_ffe = [300, 0, 0]; taps_ffe = [300, 0, 0];
taps_dfe = [5, 0, 0]; taps_dfe = [0, 0, 0];
M = 4; M = 4;
trlength = 4096*4; trlength = 4096*4;
x = 225:10:285; x = 225:10:285;
BER_PAM_4 = []; BER_PAM_4 = [];
filter_length = 210;
num_signal = 11;
our_signal = 1;
for eq_method = 2 for eq_method = 2
for j = 4 for j = 4
BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method); BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal);
BER_PAM_4 = [BER_PAM_4, BER_run]; BER_PAM_4 = [BER_PAM_4, BER_run];
save_and_append('meineDB.sqlite', 'BER_PAM_4_Save_and_Append', eq_method, num_signal, BER_run, x)
end end
save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_4_DFE_' + string(eq_method) + '.mat', 'x', 'BER_PAM_4')
BER_PAM_4 = []; BER_PAM_4 = [];
end end
%% %%
x = 225:10:285; x = 0:5:40;
for k = 1:4 for k = 2
BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\BER_PAM_4_' + string(k) + '.mat'); BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_DFE_Tap_Sweep_' + string(k) + '.mat');
BER = BER.BER_PAM_4; BER_values = BER.BER_PAM_4;
figure(202120) figure(202120)
plot(x, BER, '-o','LineWidth',1.75); plot(x, BER_values, '-o','LineWidth',1.75);
hold on hold on
end end
old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4]; % old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
old_BER = 10.^(old_BER); % old_BER = 10.^(old_BER);
plot(x, old_BER, '-o','LineWidth',1.75) % plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5); h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5); h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
@@ -42,16 +45,16 @@ h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven % Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ... legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ... 'Interpreter','latex', ...
'Location','southwest', 'FontSize', 14) 'Location','northwest', 'FontSize', 14)
% FEC Labels direkt im Plot % FEC Labels direkt im Plot
text(286,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex') text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(285,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex') text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(282.5,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex') text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(287,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex') text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex') xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
ylabel('BER', 'Interpreter','latex') ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
% title('BER for PAM-4', 'Interpreter','latex') % title('BER for PAM-4', 'Interpreter','latex')
grid minor grid minor

10
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_baud_rate_sweep.m
View File

@@ -10,20 +10,22 @@ trlength = 4096*4;
x = 4:1:8; x = 4:1:8;
BER_PAM_4 = []; BER_PAM_4 = [];
Alpha_PAM_4 = []; Alpha_PAM_4 = [];
filter_length = 210;
num_signal = 11;
for method = 1:4 for method = 1:4
for i = 1:5 for i = 1:length(power)
[BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(i), power(i), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method); [BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(i), power(i), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal);
BER_PAM_4 = [BER_PAM_4, BER_run]; BER_PAM_4 = [BER_PAM_4, BER_run];
% Alpha_PAM_4 = [Alpha_PAM_4, Alpha_run]; % Alpha_PAM_4 = [Alpha_PAM_4, Alpha_run];
end end
save('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\New Baud Rate Sweep Data\BER_PAM_4_' + string(method) + '.mat', 'x', 'BER_PAM_4') save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_' + string(method) + '.mat', 'x', 'BER_PAM_4')
BER_PAM_4 = []; BER_PAM_4 = [];
end end
%% BER %% BER
for k = 1:4 for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\Silas DSP\imdd_simulation\projects\FSO_transmission\New Baud Rate Sweep Data\BER_PAM_4_' + string(k) + '.mat'); BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_' + string(k) + '.mat');
BER = BER.BER_PAM_4; BER = BER.BER_PAM_4;
% x = BER.x; % x = BER.x;
% BER_Alpha = load(filename); % BER_Alpha = load(filename);

88
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_baud_rate_sweep_opt.m Normal file
View File

@@ -0,0 +1,88 @@
baud_rate = 4:1:8;
baud_rate = string(baud_rate);
power = [8.4, 8.4, 42.3, 8.4, 8.4];
power = string(power);
num_pf_coeff = 4;
taps_ffe = [300, 0, 0];
taps_dfe = [0, 0, 0];
M = 4;
trlength = 4096*4;
x = 4:1:8;
BER_PAM_4 = [];
BER_num_signal_sweep = [];
BER_num_signal_sweep_matrix = [];
Alpha_PAM_4 = [];
filter_length = 210;
idx_opt = [];
for method = 1:4
for j = 1:length(power)
for num_signal_sweep = 1:15
[BER_run, ~] = first_analysis_baud_rate_sweep(baud_rate(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal_sweep);
BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
% Alpha_PAM_4 = [Alpha_PAM_4, Alpha_run];
end
[BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
BER_PAM_4 = [BER_PAM_4, BER_opt];
idx_opt = [idx_opt, num_signal_opt];
BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
BER_num_signal_sweep = [];
end
save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(method) + '.mat', 'BER_PAM_4', 'BER_num_signal_sweep_matrix', 'idx_opt')
BER_PAM_4 = [];
end
%% BER
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(k) + '.mat');
BER = BER.BER_PAM_4;
% x = BER.x;
% BER_Alpha = load(filename);
% BER = BER_Alpha.BER_PAM_4;
% close all
figure(239)
plot(x, BER, '-o','LineWidth',1.75)
hold on
end
% old_BER = [-4.4, -4, -3.3, -2.7, -2.5, -2.475];
% old_BER = 10.^(old_BER);
% plot(x, old_BER, '--o','LineWidth',1)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE','FFE+PF+MLSE','DB','ML-MLSE',...
'Interpreter','latex', ...
'Location','southwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(8.2,2.3e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(8.2,3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(8.2,5.6e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(8.2,2.5e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
ylabel('BER', 'Interpreter','latex')
% title('BER for PAM-4', 'Interpreter','latex')
grid minor
% ylim([1e-4 5e-2])
xlim([3 9])
set(gca,'YScale','log')
hold off
%% Channel Alpha
% Alpha = BER_Alpha.Alpha_PAM_4;
% figure
% plot(x, Alpha, '--o','LineWidth',1)
% hold on
% xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
% ylabel('Channel Alpha', 'Interpreter','latex')
% title('Channel Alpha for PAM-4 - 300-Tap-FFE - 1 Postfilter Coefficients - 8192 Training Symbols', 'Interpreter','latex')
% grid minor
% hold off

73
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_opt.m Normal file
View File

@@ -0,0 +1,73 @@
%%
current = 225:10:285;
current = string(current);
power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power);
num_pf_coeff = 4;
taps_ffe = [300, 0, 0];
taps_dfe = [0, 0, 0];
M = 4;
trlength = 4096*4;
x = 225:10:285;
BER_PAM_4 = [];
BER_num_signal_sweep = [];
BER_num_signal_sweep_matrix = [];
filter_length = 210;
our_signal = 1;
idx_opt = [];
for eq_method = 1:4
for j = 1:length(power)
for num_signal_sweep = 1:15
BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal_sweep, our_signal);
BER_num_signal_sweep = [BER_num_signal_sweep, BER_run];
end
[BER_opt, num_signal_opt] = min(BER_num_signal_sweep);
BER_PAM_4 = [BER_PAM_4, BER_opt];
idx_opt = [idx_opt, num_signal_opt];
BER_num_signal_sweep_matrix = [BER_num_signal_sweep_matrix; BER_num_signal_sweep];
BER_num_signal_sweep = [];
end
save('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(eq_method) + '.mat', 'BER_PAM_4', 'BER_num_signal_sweep_matrix', 'idx_opt')
BER_PAM_4 = [];
idx_opt = [];
end
%%
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(k) + '.mat');
BER_values = BER.BER_PAM_4;
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
% old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
% old_BER = 10.^(old_BER);
% plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ...
'Location','northwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
% title('BER for PAM-4', 'Interpreter','latex')
grid minor
ylim([1e-4 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

64
projects/FSO_transmission/Evaluation Scripts/evalscript_pam_4_saa.m Normal file
View File

@@ -0,0 +1,64 @@
%%
current = 225:10:285;
current = string(current);
power = [28.02, 33.2, 37.5, 42.3, 46.3, 49.3, 53.4];
power = string(power);
num_pf_coeff = 4;
taps_ffe = [300, 0, 0];
taps_dfe = [5, 0, 0];
M = 4;
trlength = 4096*4;
x = 225:10:285;
BER_PAM_4 = [];
filter_length = 210;
num_signal = 11;
our_signal = 1;
for eq_method = 2
for j = 4
BER_run = first_analysis_ber(current(j), power(j), num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal);
BER_PAM_4 = [BER_PAM_4, BER_run];
save_and_append('FSO_DB.sqlite', 'BER_PAM_4_Save_and_Append', 0, eq_method, num_signal, BER_run, x, taps_ffe)
end
BER_PAM_4 = [];
end
%%
x = 0:5:40;
for k = 2
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Save_and_Append.mat');
BER_values = BER.BER_PAM_4;
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
% old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
% old_BER = 10.^(old_BER);
% plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ...
'Location','northwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(23,2.6e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(23,2.6e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(23.5,6.5e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(23,1.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex', 'FontSize', 14)
ylabel('BER', 'Interpreter','latex', 'FontSize', 14)
% title('BER for PAM-4', 'Interpreter','latex')
grid minor
ylim([1e-4 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

3
projects/FSO_transmission/Evaluation Scripts/execution_script_optimal_signal_trace_selection_sweep.m Normal file
View File

@@ -0,0 +1,3 @@
run('evalscript_pam_2_opt')
run('evalscript_pam_4_opt')
run('evalscript_pam_4_baud_rate_sweep_opt')

29
projects/FSO_transmission/Evaluation Scripts/first_analysis_baud_rate_sweep.m
View File

@@ -1,4 +1,4 @@
function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method) function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, method, filter_length, num_signal)
%% %%
close all close all
base = "C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\Sweep Data\"; base = "C:\Users\magf\Desktop\Desktop\MATLAB-Zeugs\FSO Equalizer\Sweep Data\";
@@ -90,7 +90,7 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
% timing sync -> at this point we still have no symbol timing recovery, we % timing sync -> at this point we still have no symbol timing recovery, we
% try to do this with 2sps EQ! % 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_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_1 = Rx_synced_cell{num_signal};
% Rx_Time_Rec = Rx_matched; % Rx_Time_Rec = Rx_matched;
% Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1); % Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1);
@@ -172,18 +172,6 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
% Channel_Alpha = mlse_results.metrics.Alpha; % Channel_Alpha = mlse_results.metrics.Alpha;
elseif method == 3 elseif method == 3
%% -------------------- 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",80,"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);
fprintf('ML-based MLSE:\n');
fprintf('My EQ: %.1e \n',ml_mlse_results.metrics.BER);
fprintf('Paper: %.1e \n \n',ber_in_paper);
BER = ml_mlse_results.metrics.BER;
elseif method == 4
%% -------------------- DB target -------------------- %% -------------------- DB target --------------------
mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels); mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
@@ -197,6 +185,19 @@ function [BER, Channel_Alpha] = first_analysis_baud_rate_sweep(baud_rate, power,
fprintf('My EQ: %.1e \n',dbt_results.metrics.BER); fprintf('My EQ: %.1e \n',dbt_results.metrics.BER);
fprintf('Paper: %.1e \n \n',ber_in_paper); fprintf('Paper: %.1e \n \n',ber_in_paper);
BER = dbt_results.metrics.BER; BER = dbt_results.metrics.BER;
elseif method == 4
%% -------------------- 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",filter_length,"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);
fprintf('ML-based MLSE:\n');
fprintf('My EQ: %.1e \n',ml_mlse_results.metrics.BER);
fprintf('Paper: %.1e \n \n',ber_in_paper);
BER = ml_mlse_results.metrics.BER;
end end
Channel_Alpha = 0; Channel_Alpha = 0;
end end

23
projects/FSO_transmission/Evaluation Scripts/first_analysis_ber.m
View File

@@ -1,4 +1,4 @@
function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method) function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe, taps_dfe, M, trlength, eq_method, filter_length, num_signal, our_signal, weighted_DFE)
%% %%
close all close all
@@ -12,9 +12,11 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
if M == 2 if M == 2
tx_data_path = fullfile(base, "14G_PAM2\tx_info\tx_info_PAM2_14Gbd0.75RRC.mat"); 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=" + current + "mA_RoP=" + power + "mW_L=31m_PS=RRC_rolloff=0.75_Mode=Rise.mat"); filename = fullfile(base, "14G_PAM2\M=2_Rs=1.4e10_Fs=8e10_I=" + current + "mA_RoP=" + power + "mW_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 elseif M == 4
tx_data_path = fullfile(base, "6G_PAM4\tx_info\tx_info_PAM4_6Gbd0.6RRC.mat"); 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=" + current + "mA_RoP=" + power + "mW_L=31m_PS=RRC_rolloff=0.6_Mode=Rise.mat"); filename = fullfile(base, "6G_PAM4\M=4_Rs=6e9_Fs=8e10_I=" + current + "mA_RoP=" + power + "mW_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 end
if mode == 1 if mode == 1
@@ -92,7 +94,11 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
% timing sync -> at this point we still have no symbol timing recovery, we % timing sync -> at this point we still have no symbol timing recovery, we
% try to do this with 2sps EQ! % 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_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_1 = Rx_synced_cell{num_signal};
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{num_signal};
% Rx_Time_Rec = Rx_matched; % Rx_Time_Rec = Rx_matched;
% Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1); % Rx_Time_Rec = Timing_Recovery_Move_It('f_sim', 28e9, 'gamma', 0.1).process(Rx_matched_1);
@@ -106,13 +112,21 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
end end
Rx_Time_Rec.fs = fsym; Rx_Time_Rec.fs = fsym;
Rx_Time_Rec = Rx_Time_Rec.normalize('mode','rms');
Rx_tr_mf = Rx_tr_mf.normalize('mode','rms');
% Rx_Time_Rec.signal = resample(Rx_Time_Rec.signal, 12e9, 6e9); % Rx_Time_Rec.signal = resample(Rx_Time_Rec.signal, 12e9, 6e9);
% Rx_matched_1.plot("fignum",231231) % Rx_matched_1.plot("fignum",231231)
% Rx_Time_Rec.plot("fignum",231231) % Rx_Time_Rec.plot("fignum",231231)
%% not working.. %% not working..
if our_signal
Rx_synced = Rx_Time_Rec; Rx_synced = Rx_Time_Rec;
else
Rx_synced = Rx_tr_mf;
end
% Rx_synced = Rx_Time_Rec;
% Rx_synced = Rx_synced_cell{1}; % Rx_synced = Rx_synced_cell{1};
len_tr = trlength; len_tr = trlength;
mu_ffe1 = 0.0001; mu_ffe1 = 0.0001;
@@ -162,7 +176,8 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
eq_v = EQ("Ne",taps_ffe,"Nb",taps_dfe, ... eq_v = EQ("Ne",taps_ffe,"Nb",taps_dfe, ...
"training_length",len_tr,"training_loops",5,"dd_loops",5, ... "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
"K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ... "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
"FFEmu",0,"plotfinal",0,"ideal_dfe",1); "FFEmu",0,"plotfinal",0,"ideal_dfe",0,'weighted_DFE',1,'weighted_DFE_d_min',0.5, ...
'weighted_DFE_mode','I2','weighted_DFE_I_mode',weighted_DFE,'PDFE_coefficient',0.01);
pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1); pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels); mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels);
@@ -194,7 +209,7 @@ function BER_value = first_analysis_ber(current, power, num_pf_coeff, taps_ffe,
%% -------------------- ML-based MLSE (L=2) -------------------- %% -------------------- ML-based MLSE (L=2) --------------------
ml_mlse_equalizer = ML_MLSE("epochs_tr",150,"epochs_dd",1, ... 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",80,"sps",1, ... "len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",filter_length,"sps",1, ...
"traceback_depth",256,"L",1,"delta",4,"adaptive_mu",0); "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); [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);

72
projects/FSO_transmission/Evaluation Scripts/first_analysis_tr_mf.m
View File

@@ -98,7 +98,7 @@ H_transfer = Rx_spectrum.signal./Tx_spectrum.signal;
H_inv = 1./H_transfer; H_inv = 1./H_transfer;
%Number of Samples/Symbol after Matched Filter %Number of Samples/Symbol after Matched Filter
Kov = 14; Kov = 40;
Scope_sig = Scope_sig.resample('fs_in',fs,'fs_out',Kov*fsym); Scope_sig = Scope_sig.resample('fs_in',fs,'fs_out',Kov*fsym);
@@ -114,7 +114,7 @@ Rx_matched.spectrum("displayname",'Signal after matched filter','fignum',1);
data_tr_mf = Electricalsignal(data_tr_mf.Results, "fs", fsym); 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_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}; Rx_tr_mf = Rx_synced_cell_tr_mf{11};
% timing sync -> at this point we still have no symbol timing recovery, we % timing sync -> at this point we still have no symbol timing recovery, we
% try to do this with 2sps EQ! % try to do this with 2sps EQ!
@@ -123,7 +123,7 @@ Rx_tr_mf = Rx_synced_cell_tr_mf{1};
% Rx_matched = Rx_matched.resample("fs_out",2*fsym); % Rx_matched = Rx_matched.resample("fs_out",2*fsym);
[~,Rx_synced_cell,inverted,sequenceFound,sequenceStarts] = Rx_matched.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 1); [~,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_1 = Rx_synced_cell{11};
Rx_matched_original = Rx_synced_cell{1}; Rx_matched_original = Rx_synced_cell{1};
Rx_matched_original.signal = resample(Rx_matched_original.signal,1,Kov); Rx_matched_original.signal = resample(Rx_matched_original.signal,1,Kov);
@@ -135,14 +135,15 @@ Time_Rec = 1;
if Time_Rec if Time_Rec
% [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); % [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);
% [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, Timing_Error_MG] = Godard_Timing_Recovery('mode',2,'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); % Rx_Time_Rec = Rx_Time_Rec.resample('fs_in',Kov*fsym,'fs_out',fsym);
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); Rx_Time_Rec = MaxVar_Timing_Recovery('mode',0,'fsym',fsym,'fadc',Kov*fsym,'num_tau',Kov*2048,'sps',Kov,'comp_signal',Rx_tr_mf,'comp_mode',0).process(Rx_matched_1);
sps = 1; sps = 1;
else else
Rx_Time_Rec = Rx_matched_1; Rx_Time_Rec = Rx_matched_1;
sps = 1; sps = 1;
end end
@@ -188,7 +189,7 @@ for our_signal = 1
end end
% Rx_synced = Rx_Time_Rec; % Rx_synced = Rx_Time_Rec;
% Rx_synced = Rx_synced_cell{1}; % Rx_synced = Rx_synced_cell{1};
len_tr = 4096*2; len_tr = 4096*4;
mu_ffe1 = 0.0001; mu_ffe1 = 0.0001;
mu_ffe2 = 0.0008; mu_ffe2 = 0.0008;
mu_ffe3 = 0.001; mu_ffe3 = 0.001;
@@ -232,40 +233,41 @@ for our_signal = 1
% end % end
%% -------------------- VNLE + MLSE -------------------- %% -------------------- VNLE + MLSE --------------------
% pf_ncoeffs = 4; pf_ncoeffs = 4;
% eq_v = EQ("Ne",[300, 0, 0],"Nb",[0, 0, 0], ... eq_v = EQ("Ne",[300, 0, 0],"Nb",[2, 0, 0], ...
% "training_length",len_tr,"training_loops",5,"dd_loops",5, ... "training_length",len_tr,"training_loops",5,"dd_loops",5, ...
% "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ... "K",sps,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
% "FFEmu",0,"plotfinal",0,"ideal_dfe",1, ... "FFEmu",0,"plotfinal",0,"ideal_dfe",0, ...
% 'weighted_DFE',0,'weighted_DFE_d_min',0.5,'weighted_DFE_mode','R2','weighted_DFE_I_mode',[5,0.5,0.6]); 'weighted_DFE',1,'weighted_DFE_d_min',0.5,'weighted_DFE_mode','I2','weighted_DFE_I_mode',[1,0.1,0.1], ...
% % eq_v = FFE_DFE('ffe_order',300,'dfe_order',5,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5, ... 'PDFE_coefficient',0.01);
% % 'ffe_mu_dd',mu_ffe,'ffe_mu_tr',0,'dfe_mu_dd',mu_dfe,'dfe_mu_tr',0.005,'sps',sps,'decide',0); % eq_v = FFE_DFE('ffe_order',300,'dfe_order',5,'len_tr',len_tr,'epochs_tr',5,'epochs_dd',5, ...
% pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1); % 'ffe_mu_dd',mu_ffe,'ffe_mu_tr',0,'dfe_mu_dd',mu_dfe,'dfe_mu_tr',0.005,'sps',sps,'decide',0);
% mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0,"eth_style",mapping_style).levels); 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) -------------------- [vnle_results, mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Rx_synced, Symbols, Bits, ...
ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ... "precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", mapping_style);
"len_tr",length(Rx_synced),"mu_dd",0.03,"mu_tr",0.03,"order",11,"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); mlse_results.metrics.print
if our_signal if our_signal
fprintf('Our Signal: %.1e \n',ml_mlse_results.metrics.BER); fprintf('Our Signal: %.1e \n',mlse_results.metrics.BER);
fprintf('Paper: %.1e \n \n',ber_in_paper); fprintf('Paper: %.1e \n \n',ber_in_paper);
else else
fprintf('Their EQ: %.1e \n',ml_mlse_results.metrics.BER); fprintf('Their Signal: %.1e \n',mlse_results.metrics.BER);
fprintf('Paper: %.1e \n \n',ber_in_paper); fprintf('Paper: %.1e \n \n',ber_in_paper);
end end
%% -------------------- 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",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 end

61
projects/FSO_transmission/Evaluation Scripts/plotscript_pam_2_optimal.m Normal file
View File

@@ -0,0 +1,61 @@
%%
x = 225:10:285;
averaging_over_signal_traces = 1;
all_BER_plots = 0;
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_2_Optimal' + string(k) + '.mat');
BER_values = BER.BER_PAM_2;
idx_opt = BER.idx_opt;
BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
disp(idx_opt)
BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*7+1:k*7),:);
if averaging_over_signal_traces
for i = 1:size(BER_values,2)
BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
end
end
if all_BER_plots
figure;
hold on
for i = 1:size(BER_num_signal_sweep_matrix,1)
plot(BER_num_signal_sweep_matrix(i,:))
end
hold off
end
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
old_BER = [-1.5, -1.75, -2, -2.3, -2.6, -2.25, -1.95];
old_BER = 10.^(old_BER);
plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ...
'Location','southwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(221,3.3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(221,5.4e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(231,2.4e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
ylabel('BER', 'Interpreter','latex')
% title('BER for PAM-2', 'Interpreter','latex')
grid minor
ylim([1e-4 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

61
projects/FSO_transmission/Evaluation Scripts/plotscript_pam_4_optimal.m Normal file
View File

@@ -0,0 +1,61 @@
%%
x = 225:10:285;
averaging_over_signal_traces = 1;
all_BER_plots = 0;
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Optimal' + string(k) + '.mat');
BER_values = BER.BER_PAM_4;
idx_opt = BER.idx_opt;
BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
disp(idx_opt)
BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*7+1:k*7),:);
if averaging_over_signal_traces
for i = 1:size(BER_values,2)
BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
end
end
if all_BER_plots
figure;
hold on
for i = 1:size(BER_num_signal_sweep_matrix,1)
plot(BER_num_signal_sweep_matrix(i,:))
end
hold off
end
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
old_BER = [-1.6, -1.85, -2.2, -2.45, -2.3, -2, -1.4];
old_BER = 10.^(old_BER);
plot(x, old_BER, '-o','LineWidth',1.75)
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', 'BER Paper', ...
'Interpreter','latex', ...
'Location','southwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(221,2.2e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(221,3.2e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(221,5.7e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(221,2.5e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Laser Bias Current [mA]', 'Interpreter','latex')
ylabel('BER', 'Interpreter','latex')
% title('BER for PAM-2', 'Interpreter','latex')
grid minor
ylim([3e-5 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

59
projects/FSO_transmission/Evaluation Scripts/plotscript_pam_4_symbol_rate_sweep_optimal.m Normal file
View File

@@ -0,0 +1,59 @@
%%
x = 4:1:8;
averaging_over_signal_traces = 1;
all_BER_plots = 0;
for k = 1:4
BER = load('C:\Users\magf\Desktop\Desktop\Projekte\FSO\Data\BER_PAM_4_Baud_Rate_Sweep_Optimal_' + string(k) + '.mat');
BER_values = BER.BER_PAM_4;
idx_opt = BER.idx_opt;
BER_num_signal_sweep_matrix = BER.BER_num_signal_sweep_matrix;
disp(idx_opt)
BER_num_signal_sweep_matrix = BER_num_signal_sweep_matrix(((k-1)*5+1:k*5),:);
if averaging_over_signal_traces
for i = 1:size(BER_values,2)
BER_values(i) = mean(BER_num_signal_sweep_matrix(i,:));
end
end
if all_BER_plots
figure;
hold on
for i = 1:size(BER_num_signal_sweep_matrix,1)
plot(BER_num_signal_sweep_matrix(i,:))
end
hold off
end
figure(202120)
plot(x, BER_values, '-o','LineWidth',1.75);
hold on
end
h1 = yline(2e-2, ':k', 'LineWidth',1.5);
h2 = yline(3.8e-3,':b', 'LineWidth',1.5);
h3 = yline(4.85e-3,':g', 'LineWidth',1.5);
h4 = yline(2.2e-4,':r', 'LineWidth',1.5);
% Legende NUR für Kurven
legend('FFE', 'FFE+PF+MLSE', 'DB', 'ML-MLSE', ...
'Interpreter','latex', ...
'Location','southwest', 'FontSize', 14)
% FEC Labels direkt im Plot
text(3.2,2.3e-2,'o-FEC','Color','k','FontSize', 14, 'Interpreter','latex')
text(3.2,3e-3,'HD-FEC','Color','b','FontSize', 14, 'Interpreter','latex')
text(3.2,5.9e-3,'KP4+Hamming','Color','g','FontSize', 14,'Interpreter','latex')
text(3.2,2.7e-4,'KP4','Color','r','FontSize', 14,'Interpreter','latex')
xlabel('Symbol Rate [GBd]', 'Interpreter','latex')
ylabel('BER', 'Interpreter','latex')
% title('BER for PAM-2', 'Interpreter','latex')
grid minor
xlim([3 9])
ylim([5e-7 5e-1])
set(gca,'YScale','log')
% beautifyBERplot
hold off

4
projects/FSO_transmission/FSO_timing_recovery_minimal_example.m
View File

@@ -236,8 +236,8 @@ for our_signal = 1
% end % end
%% -------------------- ML-based MLSE (L=2) -------------------- %% -------------------- ML-based MLSE (L=2) --------------------
ml_mlse_equalizer = ML_MLSE("epochs_tr",100,"epochs_dd",1, ... 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",80,"sps",sps, ... "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); "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); [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Rx_synced, Symbols, Bits,"precode_mode",duob_mode,"eth_style_symbol_mapping",mapping_style);