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Andreas Tsouchlos
2026-03-23 00:58:52 +01:00
parent 3b9f108ee5
commit fd0a354cf9
1 changed files with 4 additions and 3 deletions
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7
src/thesis/chapters/2_fundamentals.tex
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@@ -128,7 +128,7 @@ One approach is to use the \ac{ml} criterion \cite[Sec.
.
\end{align*}
Finally, we differentiate between \textit{soft decision} decoding, where
$\bm{y} \in \mathbb{R}^n$ and \textit{hard decision} decoding, where
$\bm{y} \in \mathbb{R}^n$, and \textit{hard decision} decoding, where
$\bm{y} \in \mathbb{F}_2^n$ \cite[Sec. 1.5.1.3]{ryan_channel_2009}.
%
\begin{figure}[h]
@@ -146,9 +146,9 @@ $\bm{y} \in \mathbb{F}_2^n$ \cite[Sec. 1.5.1.3]{ryan_channel_2009}.
]
\node (in) {};
\node[box, right=of in] (enc) {Encoder};
\node[box, minimum width=23mm, right=of enc] (mod) {Modulator};
\node[box, minimum width=25mm, right=of enc] (mod) {Modulator};
\node[box, below right=of mod] (cha) {Channel};
\node[box, minimum width=23mm, below left=of cha] (dem) {Demodulator};
\node[box, minimum width=25mm, below left=of cha] (dem) {Demodulator};
\node[box, left=of dem] (dec) {Decoder};
\node[left=of dec] (out) {};
@@ -173,6 +173,7 @@ $\bm{y} \in \mathbb{F}_2^n$ \cite[Sec. 1.5.1.3]{ryan_channel_2009}.
\red{
\begin{itemize}
\item Use \cite[Ch. 5]{ryan_channel_2009} as a reference
\item Core concept (Large $n$ with manageable complexity)
\item Tanner graphs, VNs and CNs
\end{itemize}