Publication

Efficient list decoding of Reed-Solomon codes for message recovery in the presence of high noise levels

Related publications (43)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Optimization of LPN Solving Algorithms

Serge Vaudenay, Sonia Mihaela Bogos

In this article we focus on constructing an algorithm that automatizes the generation of LPN solving algorithms from the considered parameters. When searching for an algorithm to solve an LPN instance, we make use of the existing techniques and optimize th ...

Springer-Verlag Berlin2016

Sparse Probabilistic Models

Andrei Giurgiu

This thesis is concerned with a number of novel uses of spatial coupling, applied to a class of probabilistic graphical models. These models include error correcting codes, random constraint satisfaction problems (CSPs) and statistical physics models calle ...

EPFL2015

Re-proving Channel Polarization Theorems

Mine Alsan

The general subject considered in this thesis is a recently discovered coding technique, polar coding, which is used to construct a class of error correction codes with unique properties. In his ground-breaking work, Arikan proved that this class of codes, ...

EPFL2015

Density Evolution for Min-Sum Decoding of LDPC Codes Under Unreliable Message Storage

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming

We analyze the performance of quantized min-sum decoding of low-density parity-check codes under unreliable message storage. To this end, we introduce a simple bit-level error model and show that decoder symmetry is preserved under this model. Subsequently ...

Institute of Electrical and Electronics Engineers2014

Generalized Codes on Graphs and Applications in Content Distribution

Masoud Alipour Babaei

The contribution of this thesis is twofold. In the first part, we generalize and analyze two classes of error correcting codes: LDPC codes and product codes. We generalize graphical codes by considering checks being arbitrary codes instead of single pariti ...

EPFL2013

A Class of Generalized RS-Codes with Faster Encoding and Decoding Algorithms

Mohammad Amin Shokrollahi

In this paper we study a particular class of generalized Reed-Solomon codes and introduce encoding and decoding algorithms for such codes that speed up current hardware implementations by a factor p wherein p can be any divisor of the size of the multiplic ...

Ieee2013

Polar Codes: Finite Length Implementation, Error Correlations and Multilevel Modulation

Shannon, in his seminal work, formalized the transmission of data over a communication channel and determined its fundamental limits. He characterized the relation between communication rate and error probability and showed that as long as the communicatio ...

2012

Error control coding for orthogonal differential vector signaling

Mohammad Amin Shokrollahi, Harm Cronie

Using a transformation based, at least in part, on a non-simple orthogonal matrix, data may be transmitted over a data bus in a manner that is resilient to one or more types of signal noise, that does not require a common reference at the transmission and ...

2011

Polar codes for channel and source coding

Satish Babu Korada

The two central topics of information theory are the compression and the transmission of data. Shannon, in his seminal work, formalized both these problems and determined their fundamental limits. Since then the main goal of coding theory has been to find ...

EPFL2009

Linear Universal Decoder for Compound Discrete Memoryless Channels

Rethnakaran Pulikkoonattu

Shannon in his seminal work \cite{paper:shannon} formalized the framework on the problem of digital communication of information and storage. He quantified the fundamental limits of compression and transmission rates. The quantity \textit{channel capacity} ...

2009