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This paper outlines a three-step procedure for determining the low bit error rate performance curve of a wide class of LDPC codes of moderate length. The traditional method to estimate code performance in the higher SNR region is to use a…

Information Theory · Computer Science 2007-07-13 Chad A. Cole , Stephen G. Wilson , Eric. K. Hall , Thomas R. Giallorenzi

Random linear codes are a workhorse in coding theory, and are used to show the existence of codes with the best known or even near-optimal trade-offs in many noise models. However, they have little structure besides linearity, and are not…

Computational Complexity · Computer Science 2024-07-11 Venkatesan Guruswami , Jonathan Mosheiff

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

Information Theory · Computer Science 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

The Consultative Committee for Space Data Systems (CCSDS) 141.11-O-1 Line Product Code (LPC) provides a rare opportunity to compare maximum-likelihood decoding and message passing. The LPC considered in this paper is intended to serve as…

Information Theory · Computer Science 2021-11-16 Jonathan Nguyen , Linfang Wang , Chester Hulse , Sahil Dani , Amaael Antonini , Todd Chauvin , Divsalar Dariush , Richard Wesel

The design and implementation of error correcting codes has long been informed by two fundamental results: Shannon's 1948 capacity theorem, which established that long codes use noisy channels most efficiently; and Berlekamp, McEliece, and…

Information Theory · Computer Science 2024-10-30 Ken R. Duffy , Muriel Médard , Wei An

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

A new lower bound on the error probability of maximum likelihood decoding of a binary code on a binary symmetric channel was proved in Barg and McGregor (2004, cs.IT/0407011). It was observed in that paper that this bound leads to a new…

Information Theory · Computer Science 2007-07-13 Alexander Barg

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

Sparse random linear network coding (SRLNC) used as a class of erasure codes to ensure the reliability of multicast communications has been widely investigated. However, an exact expression for the decoding success probability of SRLNC is…

Information Theory · Computer Science 2021-08-27 WenLin Chen , Fang Lu , Yan Dong

This paper addresses the issue of design of low-rate sparse-graph codes with linear minimum distance in the blocklength. First, we define a necessary condition which needs to be satisfied when the linear minimum distance is to be ensured.…

Information Theory · Computer Science 2010-10-12 Iryna Andriyanova , Jean-Pierre Tillich

In this work it is shown that locally repairable codes (LRCs) can be list-decoded efficiently beyond the Johnson radius for a large range of parameters by utilizing the local error-correction capabilities. The corresponding decoding radius…

Information Theory · Computer Science 2020-09-16 Lukas Holzbaur , Sven Puchinger , Antonia Wachter-Zeh

In this paper, we tackle for the first time the problem of maximum likelihood (ML) estimation of the signal-to-noise ratio (SNR) parameter over time-varying single-input multiple-output (SIMO) channels. Both the data-aided (DA) and the…

Applications · Statistics 2014-11-19 Faouzi Bellili , Rabii Meftehi , Sofiene Affes , Alex Stephenne

This paper studies maximum likelihood(ML) decoding in error-correcting codes as rational maps and proposes an approximate ML decoding rule by using a Taylor expansion. The point for the Taylor expansion, which will be denoted by $p$ in the…

Dynamical Systems · Mathematics 2010-06-30 Kazunori Hayashi , Yasuaki Hiraoka

A common problem on sequential-type decoding is that at the signal-to-noise ratio (SNR) below the one corresponding to the cutoff rate, the average decoding complexity per information bit and the required stack size grow rapidly with the…

Information Theory · Computer Science 2007-07-13 Shin-Lin Shieh , Po-Ning Chen , Yunghsiang S. Han

I will show that there is a deep relation between error-correction codes and certain mathematical models of spin glasses. In particular minimum error probability decoding is equivalent to finding the ground state of the corresponding spin…

Condensed Matter · Physics 2016-08-31 Nicolas Sourlas

Selection of descent direction at a point plays an important role in numerical optimization for minimizing a real valued function. In this article, a descent sequence is generated for the functions with bounded parameters to obtain a…

Optimization and Control · Mathematics 2019-07-24 Priyanka Roy , Geetanjali Panda

This paper concerns the maximum coding rate at which data can be transmitted over a noncoherent, single-antenna, Rayleigh block-fading channel using an error-correcting code of a given blocklength with a block-error probability not…

Information Theory · Computer Science 2020-03-31 Alejandro Lancho , Tobias Koch , Giuseppe Durisi

We consider the problem of calculating the logical error probability for a stabilizer quantum code subject to random Pauli errors. To access the regime of large code distances where logical errors are extremely unlikely we adopt the…

Quantum Physics · Physics 2013-12-19 Sergey Bravyi , Alexander Vargo

Upper and lower bounds on the error probability of linear codes under maximum-likelihood (ML) decoding are shortly surveyed and applied to ensembles of codes on graphs. For upper bounds, focus is put on Gallager bounding techniques and…

Information Theory · Computer Science 2007-07-13 Igal Sason , Shlomo Shamai

We introduce an algorithm for approximating the codebook probability that is compatible with all successive cancellation (SC)-based decoding algorithms, including SC list (SCL) decoding. This approximation is based on an auxiliary…

Information Theory · Computer Science 2025-12-18 Peihong Yuan , Ken R. Duffy , Muriel Médard