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This is a tale of two linear programming decoders, namely channel coding linear programming decoding (CC-LPD) and compressed sensing linear programming decoding (CS-LPD). So far, they have evolved quite independently. The aim of the present…

Information Theory · Computer Science 2009-10-08 Alexandros G. Dimakis , Pascal O. Vontobel

Linear operator broadcast channel (LOBC) models the scenario of multi-rate packet broadcasting over a network, when random network coding is applied. This paper presents the framework of algebraic coding for LOBCs and provides a…

Information Theory · Computer Science 2011-10-19 Yimin Pang , Thomas Honold

Channel coding over arbitrarily-permuted parallel channels was first studied by Willems et al. (2008). This paper introduces capacity-achieving polar coding schemes for arbitrarily-permuted parallel channels where the component channels are…

Information Theory · Computer Science 2015-03-17 Eran Hof , Igal Sason , Shlomo Shamai , Chao Tian

Error correction codes are a crucial part of the physical communication layer, ensuring the reliable transfer of data over noisy channels. The design of optimal linear block codes capable of being efficiently decoded is of major concern,…

Information Theory · Computer Science 2024-05-08 Yoni Choukroun , Lior Wolf

We address the problem of bounding below the probability of error under maximum likelihood decoding of a binary code with a known distance distribution used on a binary symmetric channel. An improved upper bound is given for the maximum…

Information Theory · Computer Science 2007-07-16 Alexander Barg , Andrew McGregor

In this paper, we introduce a new way of constructing and decoding multipermutation codes. Multipermutations are permutations of a multiset that may consist of duplicate entries. We first introduce a new class of matrices called…

Information Theory · Computer Science 2014-09-29 Xishuo Liu , Stark C. Draper

The decomposition theory of matroids initiated by Paul Seymour in the 1980's has had an enormous impact on research in matroid theory. This theory, when applied to matrices over the binary field, yields a powerful decomposition theory for…

Discrete Mathematics · Computer Science 2016-11-18 Navin Kashyap

In his Ph.D. disseration, Feldman and his collaborators define the linear programming decoder for binary linear codes, which is a linear programming relaxation of the maximum-likelihood decoding problem. This decoder does not, in general,…

Combinatorics · Mathematics 2012-12-13 Nathan Axvig

The error probability of block codes sent under a non-uniform input distribution over the memoryless binary symmetric channel (BSC) and decoded via the maximum a posteriori (MAP) decoding rule is investigated. It is proved that the ratio of…

Information Theory · Computer Science 2023-05-10 Ling-Hua Chang , Po-Ning Chen , Fady Alajaji

We analyze the asymptotic performance of nonbinary spatially-coupled low-density parity-check (SC-LDPC) codes built on the general linear group, when the transmission takes place over the binary erasure channel. We propose an efficient…

Information Theory · Computer Science 2016-11-15 Amina Piemontese , Alexandre Graell i Amat , Giulio Colavolpe

A method for estimating the performance of low-density parity-check (LDPC) codes decoded by hard-decision iterative decoding algorithms on binary symmetric channels (BSC) is proposed. Based on the enumeration of the smallest weight error…

Information Theory · Computer Science 2007-07-13 Hua Xiao , Amir H. Banihashemi

Non-binary low-density parity-check (LDPC) codes have some advantages over their binary counterparts, but unfortunately their decoding complexity is a significant challenge. The iterative hard- and soft-reliability based majority-logic…

Information Theory · Computer Science 2015-06-22 Chenrong Xiong , Zhiyuan Yan

This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the…

Information Theory · Computer Science 2007-07-13 Igal Sason , Gil Wiechman

We propose a refined scaling law to predict the finite-length performance in the waterfall region of spatially coupled low-density parity-check codes over the binary erasure channel. In particular, we introduce some improvements to the…

Information Theory · Computer Science 2020-08-26 Roman Sokolovskii , Fredrik Brännström , Alexandre Graell i Amat

In this work, we consider efficient maximum-likelihood decoding of linear block codes for small-to-moderate block lengths. The presented approach is a branch-and-bound algorithm using the cutting-plane approach of Zhang and Siegel (IEEE…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Eirik Rosnes , Stefan Ruzika , Stefan Scholl

K.A.S. Immink and J.H. Weber recently defined and studied a channel with both gain and offset mismatch, modelling the behaviour of charge-leakage in flash memory. They proposed a decoding measure for this channel based on minimising Pearson…

Information Theory · Computer Science 2015-09-10 Simon R. Blackburn

We study the performance of nonbinary low-density parity-check (LDPC) codes over finite integer rings over two channels that arise from the Lee metric. The first channel is a discrete memory-less channel (DMC) matched to the Lee metric. The…

Information Theory · Computer Science 2022-10-19 Jessica Bariffi , Hannes Bartz , Gianluigi Liva , Joachim Rosenthal

Low-density parity-check (LDPC) codes are specified by graphs, and are the error correction technique of choice in many communications and data storage contexts. Message passing decoders diffuse information carried by parity bits into the…

Information Theory · Computer Science 2023-05-02 Beyza Dabak , Ece Tiryaki , Robert Calderbank , Ahmed Hareedy

Polar codes are of great interest since they are the first provably capacity-achieving forward error correction codes. To improve throughput and to reduce decoding latency of polar decoders, maximum likelihood (ML) decoding units are used…

Information Theory · Computer Science 2015-10-27 Chenrong Xiong , Jun Lin , Zhiyuan Yan

In this paper, new techniques are presented to either simplify or improve most existing upper bounds on the maximum-likelihood (ML) decoding performance of the binary linear codes over additive white Gaussian noise (AWGN) channels. Firstly,…

Information Theory · Computer Science 2015-03-19 Xiao Ma , Jia Liu , Baoming Bai
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