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Restore lost changes from pre-merge state

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magf
2026-02-02 13:38:56 +01:00
parent 005e821131
commit 7565ed0cf1
6 changed files with 7223 additions and 64 deletions
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48
Classes/04_DSP/Equalizer/EQ.m
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@@ -10,6 +10,10 @@ classdef EQ < handle
training_length %Number of training symbols
training_loops %Number of loops through sequence for training mode
ideal_dfe %Error free DFE decisions
weighted_DFE %Weighted DFE on/off
weighted_DFE_mode %Weighted DFE mode
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
DB_aim %Aim at duobinary output sequence
@@ -68,6 +72,10 @@ classdef EQ < handle
options.training_length = 1024 %Number of training symbols
options.training_loops = 1 %Number of loops through sequence for training mode
options.ideal_dfe = 0 %Error free DFE decisions
options.weighted_DFE = 0;
options.weighted_DFE_mode = 'R1';
options.weighted_DFE_d_min = 0.5;
options.weighted_DFE_I_mode = [5,0.5,0.6];
options.DB_aim %Aim at duobinary output sequence
@@ -438,6 +446,43 @@ classdef EQ < handle
dd_out(k) = constellation_in_(dd_idx);
end
% Implementation of a weighted DFE in
% order to prevent error propagation.
% For further details, study [1], chapter 3.2.2 -
% Modifications of DFE
if obj.weighted_DFE
% define new constellations
const = unique(ref_in);
% determine reliability factor gamma_k
if output_vec(m) > min(const) && output_vec(m) < max(const)
gamma_k = 1 - abs(output_vec(m) - dd_out(k));
else
gamma_k = 1;
end
% select mode
if strcmp(obj.weighted_DFE_mode,'R1')
if gamma_k >= obj.weighted_DFE_d_min
f_gamma_k = 1;
else
f_gamma_k = 0;
end
elseif strcmp(obj.weighted_DFE_mode,'R2')
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));
denom = 1+exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-1));
f_gamma_k = (1/2)*((nom/denom) - 1);
elseif strcmp(obj.weighted_DFE_mode,'I2')
nom = 1-exp(-obj.weighted_DFE_I_mode(1)*((gamma_k/obj.weighted_DFE_I_mode(2))-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);
end
% calculate weighted output
output_vec(m) = f_gamma_k.*dd_out(k)+(1-f_gamma_k).*output_vec(m);
end
if obj.Nb(1) > 0
dd_DFE(2:end) = dd_DFE(1:end-1);
@@ -739,3 +784,6 @@ classdef EQ < handle
end
end
% 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

2
Classes/04_DSP/Equalizer/ML_MLSE.m
View File

@@ -597,7 +597,7 @@ classdef ML_MLSE < handle
obj.S = obj.nSym;
obj.Nf = obj.order * obj.sps;
obj.nStates = obj.S^obj.L;
obj.nFeasible = obj.nStates * obj.S; %feasible state transitions
obj.nFeasible = obj.nStates * obj.S;
% --- Trellis mapping
obj.trellis_states = reshape(obj.constellation,1,[]);