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Related papers: Efficient Maximum-Likelihood Decoding of Linear Bl…

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The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid…

Information Theory · Computer Science 2007-07-13 M. Twitto , I. Sason , S. Shamai

A lower bound on the maximum likelihood (ML) decoding error exponent of linear block code ensembles, on the erasure channel, is developed. The lower bound turns to be positive, over an ensemble specific interval of erasure probabilities,…

Information Theory · Computer Science 2019-01-23 Enrico Paolini , Gianluigi Liva

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder,…

Information Theory · Computer Science 2018-03-14 Eliya Nachmani , Elad Marciano , Loren Lugosch , Warren J. Gross , David Burshtein , Yair Beery

A new algorithm for efficient exact maximum likelihood decoding of polar codes (which may be CRC augmented), transmitted over the binary erasure channel, is presented. The algorithm applies a matrix triangulation process on a sparse polar…

Information Theory · Computer Science 2021-06-29 Yonatan Urman , David Burshtein

The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem that is gaining relevance thanks to emerging applications in wireless communication networks. In this paper, we…

Information Theory · Computer Science 2019-03-12 Mustafa Cemil Coşkun , Giuseppe Durisi , Thomas Jerkovits , Gianluigi Liva , William Ryan , Brian Stein , Fabian Steiner

We examine LDPC codes decoded using linear programming (LP). Four contributions to the LP framework are presented. First, a new method of tightening the LP relaxation, and thus improving the LP decoder, is proposed. Second, we present an…

Information Theory · Computer Science 2016-11-17 David Burshtein , Idan Goldenberg

We consider the Additive White Gaussian Noise channel with Binary Phase Shift Keying modulation. Our aim is to enable an algebraic hard decision Bounded Minimum Distance decoder for a binary block code to exploit soft information obtained…

Information Theory · Computer Science 2009-05-18 Christian Senger , Vladimir Sidorenko , Victor Zyablov

In this paper, we develop a new decoding algorithm of a binary linear codes for symbol-pair read channels. Symbol-pair read channel has recently been introduced by Cassuto and Blaum to model channels with high write resolution but low read…

Information Theory · Computer Science 2016-12-21 Shunsuke Horii , Toshiyasu Matsushima , Shigeichi Hirasawa

This work identifies information-theoretic quantities that are closely related to the required list size on average for successive cancellation list (SCL) decoding to implement maximum-likelihood decoding over general binary memoryless…

Information Theory · Computer Science 2022-04-04 Mustafa Cemil Coşkun , Henry D. Pfister

A novel and efficient neural decoder algorithm is proposed. The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group. By combining neural belief propagation with permutations from the Automorphism…

Information Theory · Computer Science 2018-01-10 Eliya Nachmani , Yaron Bachar , Elad Marciano , David Burshtein , Yair Be'ery

In this paper, we propose a methodology to compute the optimal finite-length coding rate for random linear network coding schemes over a line network. To do so, we first model the encoding, reencoding, and decoding process of different…

Networking and Internet Architecture · Computer Science 2018-05-16 Tan Do-Duy , M. Ángeles Vázquez-Castro

Universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC's)), and various ensembles of random codes, are studied by combining the competitive minimax approach,…

Information Theory · Computer Science 2007-08-01 Yaniv Akirav , Neri Merhav

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

This study investigates the problem of learning linear block codes optimized for Belief-Propagation decoders significantly improving performance compared to the state-of-the-art. Our previous research is extended with an enhanced system…

Signal Processing · Electrical Eng. & Systems 2025-10-02 Louis-Adrien Dufrène , Quentin Lampin , Guillaume Larue

We analyze the trade-off between the undetected error probability (i.e., the probability that the channel decoder outputs an erroneous message without detecting the error) and the total error probability in the short blocklength regime. We…

Information Theory · Computer Science 2025-03-05 Alexander Sauter , A. Oguz Kislal , Giuseppe Durisi , Gianluigi Liva , Balazs Matuz , Erik G. Ström

The computational complexity of the Maximum Likelihood decoding algorithm in [1], [2] for orthogonal space-time block codes is smaller than specified.

Information Theory · Computer Science 2009-08-08 Ender Ayanoglu

We consider near maximum-likelihood (ML) decoding of short linear block codes based on neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this method significantly outperforms conventional BP decoding, the…

Information Theory · Computer Science 2020-10-26 Andreas Buchberger , Christian Häger , Henry D. Pfister , Laurent Schmalen , Alexandre Graell i Amat

Spinal codes are a type of capacity-achieving rateless codes that have been proved to approach the Shannon capacity over the additive white Gaussian noise (AWGN) channel and the binary symmetric channel (BSC). In this paper, we aim to…

Information Theory · Computer Science 2022-04-05 Aimin Li , Shaohua Wu , Jian Jiao , Ning Zhang , Qinyu Zhang

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

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
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