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In 1973, Gallager proved that the random-coding bound is exponentially tight for the random code ensemble at all rates, even below expurgation. This result explained that the random-coding exponent does not achieve the expurgation exponent…

Information Theory · Computer Science 2013-08-29 Yuval Domb , Ram Zamir , Meir Feder

The DNA storage channel is considered, in which a codeword is comprised of $M$ unordered DNA molecules. At reading time, $N$ molecules are sampled with replacement, and then each molecule is sequenced. A coded-index concatenated-coding…

Information Theory · Computer Science 2022-05-23 Nir Weinberger

We recently showed in [1] the superiority of certain structured coding matrices ensembles (such as partial row-orthogonal) for sparse superposition codes when compared with purely random matrices with i.i.d. entries, both…

Information Theory · Computer Science 2022-07-12 YuHao Liu , Teng Fu , Jean Barbier , TianQi Hou

This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error…

Information Theory · Computer Science 2007-07-13 I. Sason , I. Goldenberg

This paper studies the second-order asymptotics of the Gaussian multiple-access channel with degraded message sets. For a fixed average error probability $\varepsilon \in (0,1)$ and an arbitrary point on the boundary of the capacity region,…

Information Theory · Computer Science 2015-10-07 Jonathan Scarlett , Vincent Y. F. Tan

The performance of maximum-likelihood (ML) decoding on the binary erasure channel for finite-length low-density parity-check (LDPC) codes from two random ensembles is studied. The theoretical average spectrum of the Gallager ensemble is…

Information Theory · Computer Science 2018-11-21 Irina E. Bocharova , Boris D. Kudryashov , Vitaly Skachek , Eirik Rosnes , Øyvind Ytrehus

An additive noise channel is considered, in which the distribution of the noise is nonparametric and unknown. The problem of learning encoders and decoders based on noise samples is considered. For uncoded communication systems, the problem…

Information Theory · Computer Science 2021-11-17 Nir Weinberger

The performance of maximum-likelihood (ML) decoded binary linear block codes over the AWGN channel is addressed via the tangential-sphere bound (TSB) and two of its recent improved versions. The paper is focused on the derivation of the…

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

The trapping redundancy of a linear code is the number of rows of a smallest parity-check matrix such that no submatrix forms an $(a,b)$-trapping set. This concept was first introduced in the context of low-density parity-check (LDPC) codes…

Information Theory · Computer Science 2016-11-15 Yu Tsunoda , Yuichiro Fujiwara

For the discrete memoryless sources with a countably infinite alphabet, we prove that for any positive integer $k$, there exists a corresponding probability interval such that if the largest symbol probability $p_{1}$ falls in this…

Information Theory · Computer Science 2026-04-21 Hongyang Liu , Wei Yan

Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed…

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

New bounds on classification error rates for the error-correcting output code (ECOC) approach in machine learning are presented. These bounds have exponential decay complexity with respect to codeword length and theoretically validate the…

Machine Learning · Computer Science 2021-09-21 Hieu D. Nguyen , Mohammed Sarosh Khan , Nicholas Kaegi , Shen-Shyang Ho , Jonathan Moore , Logan Borys , Lucas Lavalva

We consider channel coding for discrete memoryless channels (DMCs) with a novel cost constraint that constrains both the mean and the variance of the cost of the codewords. We show that the maximum (asymptotically) achievable rate under the…

Information Theory · Computer Science 2025-01-23 Adeel Mahmood , Aaron B. Wagner

Consider communication over a binary-input memoryless output-symmetric channel with low density parity check (LDPC) codes and maximum a posteriori (MAP) decoding. The replica method of spin glass theory allows to conjecture an analytic…

Information Theory · Computer Science 2016-11-17 Shrinivas Kudekar , Nicolas Macris

This paper presents prefix codes which minimize various criteria constructed as a convex combination of maximum codeword length and average codeword length or maximum redundancy and average redundancy, including a convex combination of the…

Information Theory · Computer Science 2011-02-11 Charalambos D. Charalambous , Themistoklis Charalambous , Farzad Rezaei

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

A lower bound on the number of uncorrectable errors of weight half the minimum distance is derived for binary linear codes satisfying some condition. The condition is satisfied by some primitive BCH codes, extended primitive BCH codes,…

Information Theory · Computer Science 2008-04-30 Kenji Yasunaga , Toru Fujiwara

We establish a general framework for construction of small ensembles of capacity achieving linear codes for a wide range of (not necessarily memoryless) discrete symmetric channels, and in particular, the binary erasure and symmetric…

Information Theory · Computer Science 2011-07-26 Mahdi Cheraghchi

This paper shows that the logarithm of the epsilon-error capacity (average error probability) for n uses of a discrete memoryless channel is upper bounded by the normal approximation plus a third-order term that does not exceed 1/2 log n +…

Information Theory · Computer Science 2013-10-25 Marco Tomamichel , Vincent Y. F. Tan

We study channel simulation under common randomness assistance in the finite-blocklength regime and identify the smooth channel max-information as a linear program one-shot converse on the minimal simulation cost for fixed error tolerance.…

Information Theory · Computer Science 2024-10-10 Michael X. Cao , Navneeth Ramakrishnan , Mario Berta , Marco Tomamichel