Added paragraph to discussion

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Andreas Tsouchlos 2023-04-13 16:39:26 +02:00
parent 606e3e2530
commit de7b86d0ac
2 changed files with 27 additions and 7 deletions

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@ -70,6 +70,11 @@
long = maximum likelihood
}
\DeclareAcronym{MIMO} {
short = MIMO,
long = multiple-input multiple-output
}
%
% I
%

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@ -1,12 +1,15 @@
\chapter{Discussion}%
\label{chapter:discussion}
While the modified proximal decoding algorithm presented in section
\ref{sec:prox:Improved Implementation} shows some promising results, further
investigation is required to determine how different choices of parameters
affect the decoding performance.
Additionally, a more mathematically rigorous foundation for determining the
potentially wrong components of the estimate is desirable.
A modification of the implementation to reduce the memory requirements, even
at some cost with regard to the running time, would allow for the examination
of longer codes.
This in turn would make possible studying the behavior of the decoding
algorithms covered here in error-rate regions where traditional approaches
exhibit an error floor.
The decoding algorithms could then be assessed for use in very
high reliability applications, where traditional methods like \ac{BP} or the
min-sum-algorithm fall short.
As mentioned in section \ref{subsec:prox:conv_properties}, the alternating
minimization of the two gradients in the proximal decoding algorithm leads to
@ -23,6 +26,18 @@ constraints are never truly satisfied; not even after the minimization step
dealing with the constraint part of the objective function.
Despite this, an initial examination by Yanxia Lu in
\cite[Sec. 4.2.4.]{yanxia_lu_thesis} shows only limited success.
It is also important to note that while in this thesis proximal decoding was
examined with respect to its performance in \ac{AWGN} channels, in
\cite{proximal_paper} it is presented as a method applicable to non-trivial
channel models such as \ac{LDPC}-coded massive \ac{MIMO} channels, perhaps
broadening its usefulness beyond what is shown here.
While the modified proximal decoding algorithm presented in section
\ref{sec:prox:Improved Implementation} shows some promising results, further
investigation is required to determine how different choices of parameters
affect the decoding performance.
Additionally, a more mathematically rigorous foundation for determining the
potentially wrong components of the estimate is desirable.
Another interesting approach might be the combination of proximal and \ac{LP}
decoding.