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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

Determining the exact decoding error probability of linear block codes is an interesting problem. For binary BCH codes, McEliece derived methods to estimate the error probability of a simple bounded distance decoding (BDD) for BCH codes.…

Information Theory · Computer Science 2026-01-29 Sisi Miao , Jonathan Mandelbaum , Holger Jäkel , Laurent Schmalen

This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a…

Information Theory · Computer Science 2024-03-12 Shreyas Jain , V. Arvind Rameshwar , Navin Kashyap

New upper and lower bounds for the error probability over an erasure channel are provided, making use of Wei's generalized weights, hierarchy and spectra. In many situations the upper and lower bounds coincide and this allows improvement of…

Information Theory · Computer Science 2014-07-18 Leandro Cruvinel Lemes , Marcelo Firer

In this paper, we study binary constrained codes that are resilient to bit-flip errors and erasures. In our first approach, we compute the sizes of constrained subcodes of linear codes. Since there exist well-known linear codes that achieve…

Information Theory · Computer Science 2023-04-20 V. Arvind Rameshwar , Navin Kashyap

We introduce two notions of discrepancy between binary vectors, which are not metric functions in general but nonetheless capture the mathematical structure of the binary asymmetric channel. In turn, these lead to two new fundamental…

Information Theory · Computer Science 2022-01-19 Giuseppe Cotardo , Alberto Ravagnani

Consider the problem of identifying a massive number of bees, uniquely labeled with barcodes, using noisy measurements. We formally introduce this `bee-identification problem', define its error exponent, and derive efficiently computable…

Information Theory · Computer Science 2019-06-05 Anshoo Tandon , Vincent Y. F. Tan , Lav R. Varshney

We revisit the derivation of expurgated error exponents using a method of type class enumeration, which is inspired by statistical-mechanical methods, and which has already been used in the derivation of random coding exponents in several…

Information Theory · Computer Science 2013-01-18 Neri Merhav

A family of error-correcting codes is list-decodable from error fraction $p$ if, for every code in the family, the number of codewords in any Hamming ball of fractional radius $p$ is less than some integer $L$ that is independent of the…

Information Theory · Computer Science 2024-07-11 Venkatesan Guruswami , Ray Li , Jonathan Mosheiff , Nicolas Resch , Shashwat Silas , Mary Wootters

A Lagrange-dual (Gallager-style) lower bound is derived for the error exponent function of the typical random code (TRC) pertaining to the i.i.d. random coding ensemble and mismatched stochastic likelihood decoding. While the original…

Information Theory · Computer Science 2019-08-13 Neri Merhav

We derive a sphere-packing error exponent for coded transmission over discrete memoryless channels with a fixed decoding metric. By studying the error probability of the code over an auxiliary channel, we find a lower bound to the…

Information Theory · Computer Science 2022-12-29 Ehsan Asadi Kangarshahi , Albert Guillén i Fàbregas

We consider the problem of universal decoding for arbitrary unknown channels in the random coding regime. For a given random coding distribution and a given class of metric decoders, we propose a generic universal decoder whose average…

Information Theory · Computer Science 2016-11-17 Neri Merhav

We prove that a random linear code over F_q, with probability arbitrarily close to 1, is list decodable at radius (1-1/q-\epsilon) with list size L=O(1/\epsilon^2) and rate R=\Omega_q(\epsilon^2/(log^3(1/\epsilon))). Up to the…

Information Theory · Computer Science 2012-07-06 Mahdi Cheraghchi , Venkatesan Guruswami , Ameya Velingker

In this work, a likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on a soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the…

Information Theory · Computer Science 2014-04-24 Eva C. Song , Paul Cuff , H. Vincent Poor

In this work, we study the generalization capability of algorithms from an information-theoretic perspective. It has been shown that the expected generalization error of an algorithm is bounded from above by a function of the relative…

Information Theory · Computer Science 2021-10-27 Borja Rodríguez-Gálvez , Germán Bassi , Mikael Skoglund

Upper bounds on the maximum number of codewords in a binary code of a given length and minimum Hamming distance are considered. New bounds are derived by a combination of linear programming and counting arguments. Some of these bounds…

Information Theory · Computer Science 2007-07-13 Beniamin Mounits , Tuvi Etzion , Simon Litsyn

We study error bounds for linear programming decoding of regular LDPC codes. For memoryless binary-input output-symmetric channels, we prove bounds on the word error probability that are inverse doubly-exponential in the girth of the factor…

Information Theory · Computer Science 2011-04-12 Nissim Halabi , Guy Even

The reliability function of variable-rate Slepian-Wolf coding is linked to the reliability function of channel coding with constant composition codes, through which computable lower and upper bounds are derived. The bounds coincide at rates…

Information Theory · Computer Science 2016-08-08 Jun Chen , Da-ke He , Ashish Jagmohan , Luis A. Lastras-Montaño

Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an ideal maximum-distance-separable code on the binary erasure…

Information Theory · Computer Science 2008-04-21 Enrico Paolini , Gianluigi Liva , Michela Varrella , Balazs Matuz , Marco Chiani

This paper is motivated by the problem of error control in network coding when errors are introduced in a random fashion (rather than chosen by an adversary). An additive-multiplicative matrix channel is considered as a model for random…

Information Theory · Computer Science 2019-05-07 Danilo Silva , Frank R. Kschischang , Ralf Kötter
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