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Merge remote-tracking branch 'origin/main' into main

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Silas Oettinghaus
2023-10-09 15:26:16 +02:00
parent 9ca9db0722 37c3d4e23d
commit 5fa3ecff51
1 changed files with 42 additions and 56 deletions
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90
Classes/04_DSP/EQ_silas.m
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@@ -35,12 +35,15 @@ classdef EQ_silas < handle
e_dc
error_log
% coefficients
mu_dc_train
mu_ffe_train
mu_dfe_train
mu_dc_dd
mu_combined_dd
mu_ffe_dd
mu_dfe_dd
mu_combined_dd % [1st order FFE, 2nd order FFE, 3rd order FFE, all orders DFE]
delay
trainlength
@@ -74,7 +77,8 @@ classdef EQ_silas < handle
options.mu_dfe_train = 0.005;
options.mu_dc_dd = 0.01;
options.mu_combined_dd = [0.0004 0.0005 0.0006 0.0007 ];
options.mu_ffe_dd = [0.0004 0.0005 0.0006];
options.mu_dfe_dd = 0.0005;
options.dcmode = 1;
end
@@ -106,7 +110,7 @@ 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');
@@ -155,35 +159,31 @@ classdef EQ_silas < handle
m = m+1;
%get Sigal input vectors with correct length for VNLE
x_in_block = obj.x_in(obj.Ne(1)+n+(obj.sps-1):-1:n+obj.sps).';
if obj.dcmode ~= 3
x_in_block = obj.x_in(obj.Ne(1)+n+(obj.sps-1):-1:n+obj.sps).';
elseif obj.dcmode == 3
x_in_block = obj.x_in(obj.Ne(1)+n+(obj.sps-1):-1:n+obj.sps).' + obj.e_dc;
end
x_in_vnle_format = obj.calcVNLENonlinVecs(x_in_block,obj.Ie2,obj.Ie3,obj.Ne,[1,1,1]);
x_in_vnle_format = obj.calcVNLENonlinVecs(x_in_block,obj.Ie2,obj.Ie3,obj.Ne,obj.x_norm);
%get Reference input vectors with correct length for VNLE
d_block = obj.d(obj.Nb(1)-obj.delay+m-2:-1:m-obj.delay-1).';
d_vnle_format = obj.calcVNLENonlinVecs(d_block,obj.Ib2,obj.Ib3,obj.Nb,obj.d_norm);
obj.e_dfe = obj.b.' * d_vnle_format;
obj.e_ffe = obj.e.' * x_in_vnle_format;
% Calculate the Error
if obj.dcmode == 1
obj.error = obj.e_dc + obj.e_ffe - obj.e_dfe - obj.d(obj.Nb(1)-1+m-obj.delay);
elseif obj.dcmode == 2
obj.e_ffe = obj.e_ffe + obj.e_dc;
obj.error = obj.e_ffe - obj.e_dfe - obj.d(obj.Nb(1)-1+m-obj.delay);
elseif obj.dcmode == 3
obj.error = obj.e_ffe - obj.e_dfe - obj.d(obj.Nb(1)-1+m-obj.delay);
end
obj.e_dfe = obj.b.' * d_vnle_format;
%update FFE coefficients with LMS
obj.e = obj.e - obj.error*conj(x_in_vnle_format)*obj.mu_ffe_train;
% Calculate the Error
obj.error = obj.e_dc + obj.e_ffe - obj.e_dfe - obj.d(obj.Nb(1)-1+m-obj.delay);
err_track(n) = obj.error;
if obj.mu_ffe_train ~= 0
%update FFE coefficients with LMS
obj.e = obj.e - obj.error*conj(x_in_vnle_format)*obj.mu_ffe_train;
else
%update FFE coefficients with NLMS
obj.e = obj.e - obj.error*x_in_vnle_format/(x_in_vnle_format.'*x_in_vnle_format);
end
%update DFE coefficients with LMS
obj.b = obj.b + obj.mu_dfe_train*obj.error*d_vnle_format;
@@ -208,16 +208,16 @@ classdef EQ_silas < handle
m = 0;
mu_mat = diag([ones(1,obj.Ce(1))*obj.mu_combined_dd(1)... %1st order ffe
ones(1,obj.Ce(2))*obj.mu_combined_dd(2)... %2nd order ffe
ones(1,obj.Ce(3))*obj.mu_combined_dd(3)... %3rd order ffe
ones(1,sum(obj.Cb))*obj.mu_combined_dd(4)]); %all order dfe
mu_mat = diag([ones(1,obj.Ce(1))*obj.mu_ffe_dd(1)... %1st order ffe
ones(1,obj.Ce(2))*obj.mu_ffe_dd(2)... %2nd order ffe
ones(1,obj.Ce(3))*obj.mu_ffe_dd(3)... %3rd order ffe
ones(1,sum(obj.Cb))*obj.mu_dfe_dd]); %all order dfe
mu_ffe = [ones(1,obj.Ce(1))*obj.mu_combined_dd(1)... %1st order ffe
ones(1,obj.Ce(2))*obj.mu_combined_dd(2)... %2nd order ffe
ones(1,obj.Ce(3))*obj.mu_combined_dd(3)];
mu_ffe = [ones(1,obj.Ce(1))*obj.mu_ffe_dd(1)... %1st order ffe
ones(1,obj.Ce(2))*obj.mu_ffe_dd(2)... %2nd order ffe
ones(1,obj.Ce(3))*obj.mu_ffe_dd(3)];
mu_dfe = ones(1,sum(obj.Cb))*obj.mu_combined_dd(4);
mu_dfe = ones(1,sum(obj.Cb))*obj.mu_dfe_dd;
y = zeros(1,floor(obj.x_length/obj.sps));
@@ -230,41 +230,27 @@ classdef EQ_silas < handle
m=m+1;
%get Sigal input vectors with correct length for VNLE
if obj.dcmode ~= 3
x = obj.x_in(obj.Ne(1)+k-1:-1:k).';
elseif obj.dcmode == 3
x = obj.x_in(obj.Ne(1)+k-1:-1:k).' + obj.e_dc;
end
x = obj.x_in(obj.Ne(1)+k-1:-1:k).';
x_vnle = obj.calcVNLENonlinVecs(x,obj.Ie2,obj.Ie3,obj.Ne,[1,1,1]);
x_vnle = obj.calcVNLENonlinVecs(x,obj.Ie2,obj.Ie3,obj.Ne,obj.x_norm);
%combine FFE with DFE to one vector (cursor between the two sequences)
x_d = [x_vnle;-d_vnle];
%Apply filter
if obj.dcmode == 1
y(m) = obj.e_dc + x_d.'* coeff;
elseif obj.dcmode == 2 || obj.dcmode == 3
% x_ffe = obj.e.' * x_vnle;
% x_dfe = obj.b.' * d_vnle;
% y(m) = x_ffe - x_dfe;
y(m) = x_d.'* coeff;
end
y(m) = obj.e_dc + x_d.'* coeff;
%Decision
[~,symbol_idx] = min(abs(y(m) - obj.d_constellation)); % decision for closest constellation point
d_hat(k) = obj.d_constellation(symbol_idx);
%Error between FFE & DFE filtered signal and Decision
if obj.dcmode == 1 || obj.dcmode == 3
obj.error = y(m) - d_hat(k);
elseif obj.dcmode == 2
obj.error = y(m) - d_hat(k) + obj.e_dc;
end
obj.error = y(m) - d_hat(k);
%Update coefficients (both FFE and DFE)
obj.e = obj.e - obj.error * mu_ffe * conj(x_vnle);
obj.b = obj.b + obj.error * mu_dfe * conj(d_vnle);
% obj.e = obj.e - obj.error * mu_ffe * conj(x_vnle);
% obj.b = obj.b + obj.error * mu_dfe * conj(d_vnle);
% coeff = [obj.e;obj.b];
coeff = coeff - mu_mat*obj.error*conj(x_d);