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We propose several improvements for Linear Programming (LP) decoding algorithms for High Density Parity Check (HDPC) codes. First, we use the automorphism groups of a code to create parity check matrix diversity and to generate valid cuts…

Information Theory · Computer Science 2016-11-18 Alex Yufit , Asi Lifshitz , Yair Be'ery

Guessing Codeword Decoding (GCD) is a recently proposed soft-input forward error correction decoder for arbitrary binary linear codes. Inspired by recent proposals that leverage binary linear codebook structure to reduce the number of…

Information Theory · Computer Science 2024-12-23 Joseph Griffin , Peihong Yuan , Ken R. Duffy , Muriel Medard

In this paper we explore the decision regions of Linear Programming (LP) decoding. We compare the decision regions of an LP decoder, a Belief Propagation (BP) decoder and the optimal Maximum Likelihood (ML) decoder. We study the effect of…

Information Theory · Computer Science 2011-06-15 Asi Lifshitz , Yair Be'ery

Non-binary low-density parity-check codes are robust to various channel impairments. However, based on the existing decoding algorithms, the decoder implementations are expensive because of their excessive computational complexity and…

Information Theory · Computer Science 2016-11-18 Chung-Li Wang , Xiaoheng Chen , Zongwang Li , Shaohua Yang

Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of…

Information Theory · Computer Science 2016-11-17 Panu Chaichanavong , Paul H. Siegel

In order to understand the performance of a code under maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Pascal O. Vontobel

Linear programming (LP) decoding approximates maximum-likelihood (ML) decoding of a linear block code by relaxing the equivalent ML integer programming (IP) problem into a more easily solved LP problem. The LP problem is defined by a set of…

Information Theory · Computer Science 2013-01-01 Xiaojie Zhang , Paul H. Siegel

We analyze Linear Programming (LP) decoding of graphical binary codes operating over soft-output, symmetric and log-concave channels. We show that the error-surface, separating domain of the correct decoding from domain of the erroneous…

Information Theory · Computer Science 2016-11-15 Michael Chertkov , Mikhail Stepanov

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

We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density parity-check codes is the linear programming decoder. In…

Information Theory · Computer Science 2015-03-19 Shrinivas Kudekar , Jason K. Johnson , Misha Chertkov

A framework for linear-programming (LP) decoding of nonbinary linear codes over rings is developed. This framework facilitates linear-programming based reception for coded modulation systems which use direct modulation mapping of coded…

Information Theory · Computer Science 2016-11-15 Mark F. Flanagan , Vitaly Skachek , Eimear Byrne , Marcus Greferath

We discuss the performance of Low-Density-Parity-Check (LDPC) codes decoded by means of Linear Programming (LP) at moderate and large Signal-to-Noise-Ratios (SNR). Utilizing a combination of the previously introduced pseudo-codeword-search…

Information Theory · Computer Science 2007-07-13 Michael Chertkov , Mikhail Stepanov

While low-density parity-check (LDPC) codes are near capacity-achieving when paired with iterative decoders, these decoders may not output a codeword due to the existence of pseudocodewords. Thus, pseudocodewords have been studied to give…

Information Theory · Computer Science 2025-12-03 Wittawat Kositwattanarerk , Gretchen L. Matthews , Emily McMillon , Tunchanok Yutitumsatit

Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Ali E. Pusane , Pascal O. Vontobel , Daniel J. Costello

The design of low-density parity-check (LDPC) code ensembles optimized for a finite number of decoder iterations is investigated. Our approach employs EXIT chart analysis and differential evolution to design such ensembles for the binary…

Information Theory · Computer Science 2016-11-17 Ian P. Mulholland , Enrico Paolini , Mark F. Flanagan

In this paper we study the iterative decoding threshold performance of non-binary spatially-coupled low-density parity-check (NB-SC-LDPC) code ensembles for both the binary erasure channel (BEC) and the binary-input additive white Gaussian…

Information Theory · Computer Science 2016-11-18 Lai Wei , Toshiaki Koike-Akino , David G. M. Mitchell , Thomas E. Fuja , Daniel J. Costello

In Linear Programming (LP) decoding of a Low-Density-Parity-Check (LDPC) code one minimizes a linear functional, with coefficients related to log-likelihood ratios, over a relaxation of the polytope spanned by the codewords \cite{03FWK}. In…

Information Theory · Computer Science 2007-07-13 Michael Chertkov , Mikhail G. Stepanov

A low-density parity-check (LDPC) code is a linear block code described by a sparse parity-check matrix, which can be efficiently represented by a bipartite Tanner graph. The standard iterative decoding algorithm, known as belief…

Information Theory · Computer Science 2016-05-17 Sachini Jayasooriya , Sarah J. Johnson , Lawrence Ong , Regina Berretta

We develop a framework for linear-programming (LP) decoding of non-binary linear codes over rings. We prove that the resulting LP decoder has the `maximum likelihood certificate' property, and we show that the decoder output is the lowest…

Information Theory · Computer Science 2007-10-10 Mark F. Flanagan , Vitaly Skachek , Eimear Byrne , Marcus Greferath

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
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