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Error exponents characterize the exponential decay, when increasing message length, of the probability of error of many error-correcting codes. To tackle the long standing problem of computing them exactly, we introduce a general,…

Disordered Systems and Neural Networks · Physics 2007-07-16 Thierry Mora , Olivier Rivoire

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

How well can we approximate a quantum channel output state using a random codebook with a certain size? In this work, we study the quantum soft covering problem. Namely, we use a random codebook with codewords independently sampled from a…

Quantum Physics · Physics 2022-02-23 Hao-Chung Cheng , Li Gao

The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than…

Information Theory · Computer Science 2020-01-13 Nicolas Charpenay , Maël Le Treust

The error exponent of fixed-length lossy source coding was established by Marton. Ahlswede showed that this exponent can be discontinuous at a rate $R$, depending on the probability distribution $P$ of the given information source and the…

Information Theory · Computer Science 2023-04-25 Yutaka Jitsumatsu

In this work we show how an improved lower bound to the error exponent of the memoryless multiple-access (MAC) channel is attained via the use of linear codes, thus demonstrating that structure can be beneficial even in cases where there is…

Information Theory · Computer Science 2016-11-18 Eli Haim , Yuval Kochman , Uri Erez

This paper establishes the exact strong converse exponent of the soft covering problem in the classical setting. This exponent characterizes the slowest achievable convergence speed of the total variation to one when a code of rate below…

Information Theory · Computer Science 2026-04-01 Xingyi He , S. Sandeep Pradhan , Andreas Winter

We provide two results concerning the optimality of the maximum mutual information (MMI) decoder. First, we prove that the error exponents of the typical random codes under the optimal maximum likelihood (ML) decoder and the MMI decoder are…

Information Theory · Computer Science 2020-07-27 Ran Tamir , Neri Merhav

Recently, network error correction coding (NEC) has been studied extensively. Several bounds in classical coding theory have been extended to network error correction coding, especially the Singleton bound. In this paper, following the…

Information Theory · Computer Science 2010-11-08 Xuan Guang , Fang-Wei Fu , Zhen Zhang

For the information transmission over a binary symmetric channel the random coding is used. The transmission of exponential number of messages is considered. The exact decoding error probability exponent is derived. The proof is based on…

Information Theory · Computer Science 2026-05-20 Marat V. Burnashev

In this study we consider rateless coding over discrete memoryless channels (DMC) with feedback. Unlike traditional fixed-rate codes, in rateless codes each codeword is infinitely long, and the decoding time depends on the confidence level…

Information Theory · Computer Science 2012-01-30 Navot Blits

The construction of asymmetric error correcting codes is a topic that was studied extensively, however, the existing approach for code construction assumes that every codeword should tolerate $t$ asymmetric errors. Our main observation is…

Information Theory · Computer Science 2012-09-05 Hongchao Zhou , Anxiao , Jiang , Jehoshua Bruck

Error and erasure exponents for the broadcast channel with degraded message sets are analyzed. The focus of our error probability analysis is on the main receiver where, nominally, both messages are to be decoded. A two-step decoding…

Information Theory · Computer Science 2015-01-28 Vincent Y. F. Tan

Exponential error bounds for the finite-alphabet interference channel (IFC) with two transmitter-receiver pairs, are investigated under the random coding regime. Our focus is on optimum decoding, as opposed to heuristic decoding rules that…

Information Theory · Computer Science 2008-10-14 Raul Etkin , Neri Merhav , Erik Ordentlich

This paper describes universal lossless coding strategies for compressing sources on countably infinite alphabets. Classes of memoryless sources defined by an envelope condition on the marginal distribution provide benchmarks for coding…

Statistics Theory · Mathematics 2015-01-05 Stéphane Boucheron , Aurélien Garivier , Elisabeth Gassiat

An elementary proof of the attainability of random coding exponent with linear codes for additive channels is presented. The result and proof are from Hamada (Proc. ITW, Chendu, China, 2006), and the present material explains the proof in…

Information Theory · Computer Science 2010-01-13 Mitsuru Hamada

This work proves new results on the ability of binary Reed-Muller codes to decode from random errors and erasures. We obtain these results by proving improved bounds on the weight distribution of Reed-Muller codes of high degrees.…

Information Theory · Computer Science 2018-12-03 Ori Sberlo , Amir Shpilka

This paper considers error probabilities of random codes for memoryless channels in the fixed-rate regime. Random coding is a fundamental scheme to achieve the channel capacity and many studies have been conducted for the asymptotics of the…

Information Theory · Computer Science 2017-07-17 Junya Honda

The multivariate covering lemma states that given a collection of $k$ codebooks, each of sufficiently large cardinality and independently generated according to one of the marginals of a joint distribution, one can always choose one…

Information Theory · Computer Science 2016-01-22 Parham Noorzad , Michelle Effros , Michael Langberg

We prove the following results concerning the list decoding of error-correcting codes: (i) We show that for \textit{any} code with a relative distance of $\delta$ (over a large enough alphabet), the following result holds for \textit{random…

Information Theory · Computer Science 2010-01-13 Atri Rudra , Steve Uurtamo
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