ba-thesis/latex/presentations/midterm/sections/decoding_algorithms.tex

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\section{Decoding Algorithms}%
\label{sec:Decoding Algorithms}
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\subsection{Proximal Decoding}%
\label{sub:Alg Proximal Decoding}
\begin{frame}[t]
\frametitle{Proximal Decoding: General Idea}
\begin{itemize}
\item Code constraint polynomial:
\begin{align*}
h\left( \boldsymbol{x} \right) =
\underbrace{\sum_{j=1}^{n} \left( x_j^2 - 1 \right)^2}_{\text{Bipolar constraint}}
+ \underbrace{\sum_{i=1}^{m} \left[ \left(
\prod_{j\in\mathcal{A}\left( i \right)} x_j\right) -1 \right]^2}
_{\text{Parity constraint}},
\hspace{5mm}\mathcal{A}\left( i \right) \equiv \left\{
j | j\in \mathcal{J},
\boldsymbol{H}_{j,i} = 1
\right\},
i \in \mathcal{I}
\end{align*}
\item Approximation of prior PDF:
\begin{align*}
f_{\boldsymbol{X}}\left( \boldsymbol{x} \right)
= \frac{1}{\left| \mathcal{C}\left( \boldsymbol{H} \right) \right| }
\sum_{c \in \mathcal{C}\left( \boldsymbol{H} \right) }
\delta\left( \boldsymbol{x} - \boldsymbol{c} \right)
\approx \frac{1}{Z} e^{-\gamma h\left( x \right) }
\end{align*}
\item MAP rule:
\begin{align*}
\hat{\boldsymbol{x}}
= arg\max_{x\in\mathbb{R}}\left[
f_{\boldsymbol{Y}}\left( \boldsymbol{y} | \boldsymbol{x} \right)
f_{\boldsymbol{X}}\left( \boldsymbol{x} \right) \right]
= arg\max_{x\in\mathbb{R}}\left[
e^{-L\left( \boldsymbol{y} | \boldsymbol{x}\right)}
e^{-\gamma h\left( \boldsymbol{x} \right) } \right]
\end{align*}
\end{itemize}
\end{frame}
\begin{frame}[t]
\frametitle{Proximal Decoding: General Idea}
\begin{itemize}
\item Objective function:
\begin{align*}
f\left( \boldsymbol{x} \right)
= L\left( \boldsymbol{y} | \boldsymbol{x} \right)
+ \gamma h\left( \boldsymbol{x} \right),
\hspace{5mm} L\left( \boldsymbol{y} | \boldsymbol{x} \right)
= - \ln\left( f_{\boldsymbol{Y}}
\left( \boldsymbol{y} | \boldsymbol{x} \right) \right)
\end{align*}
\note{Notational difference between $f$ and $f_X$ or $f_Y$}
\item Code proximal operator \cite{proximal_algorithms}:
\begin{align*}
\text{prox}_{\gamma h} \left( \boldsymbol{x} \right) &\equiv
arg\min_{\boldsymbol{z}\in\mathbb{R}} \left(
\gamma h\left( \boldsymbol{z} \right) + \frac{1}{2} \lVert \boldsymbol{z}
- \boldsymbol{x} \rVert^2 \right)\\
&\approx \boldsymbol{x} - \gamma \nabla h\left( \boldsymbol{x} \right),
\hspace{5mm} \gamma \text{ small}
\end{align*}
\item Iterative decoding process:
\begin{align*}
\boldsymbol{r}^{\left( k+1 \right) } &= \boldsymbol{s}^{\left( k \right) }
- \omega \nabla L\left( \boldsymbol{y} | \boldsymbol{s}^{\left( k \right) }
\right), \hspace{5mm} \omega > 0
\hspace{10mm} \text{``Gradient descent step''}\\
\boldsymbol{s}^{\left( k+1 \right) } &= \boldsymbol{r}^{\left( k+1 \right) }
- \gamma \nabla h\left( \boldsymbol{r}^{\left( k+1 \right) } \right)
\hspace{22mm} \text{``Code proximal step''}
\end{align*}
\end{itemize}
\end{frame}
\begin{frame}[t, fragile]
\frametitle{Proximal Decoding: Algorithm}
\begin{itemize}
\item Resulting terative decoding algorithm \cite{proximal_paper}:
\end{itemize}
\vspace{2mm}
\begin{algorithm}[caption={}, label={}]
$\boldsymbol{s}^{\left( 0 \right)} = \boldsymbol{0}$
for $k=0$ to $K-1$ do
$\boldsymbol{r}^{\left( k+1 \right)} = \boldsymbol{s}^{(k)} - \omega \nabla L \left( \boldsymbol{s}^{(k)}; \boldsymbol{y} \right) $
Compute $\nabla h\left( \boldsymbol{r}^{\left( k+1 \right) } \right)$
$\boldsymbol{s}^{\left( k+1 \right)} = \boldsymbol{r}^{(k+1)} - \gamma \nabla h\left( \boldsymbol{r}^{\left( k+1 \right) } \right) $
$\boldsymbol{\hat{x}} = \text{sign}\left( \boldsymbol{s}^{\left( k+1 \right) } \right) $
If $\boldsymbol{\hat{x}}$ passes the parity check condition, break the loop.
end for
Output $\boldsymbol{\hat{x}}$
\end{algorithm}
\end{frame}
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\subsection{ADMM}%
\label{sub:Alg ADMM}
\begin{frame}[t]
\frametitle{ADMM Decoding: General Idea}
\todo{TODO}
\end{frame}
\begin{frame}[t]
\frametitle{ADMM Decoding: Algorithm}
\todo{TODO}
\end{frame}