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In 1973, Arimoto proved the strong converse theorem for the discrete memoryless channels stating that when transmission rate $R$ is above channel capacity $C$, the error probability of decoding goes to one as the block length $n$ of code…

Information Theory · Computer Science 2012-05-03 Yasutada Oohama

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

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

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

Exponential error bounds achievable by universal coding and decoding are derived for frame-asynchronous discrete memoryless %asynchronous multiple access channels with two senders, via the method of subtypes, a refinement of the method of…

Information Theory · Computer Science 2020-02-04 Lóránt Farkas , Tamás Kói

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

This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to…

Information Theory · Computer Science 2022-03-16 Lan V. Truong , Giuseppe Cocco , Josep Font-Segura , Albert Guillén i Fàbregas

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

This paper presents encoding and decoding algorithms for several families of optimal rank metric codes whose codes are in restricted forms of symmetric, alternating and Hermitian matrices. First, we show the evaluation encoding is the right…

Information Theory · Computer Science 2022-02-08 Wrya K. Kadir , Chunlei Li , Ferdinando Zullo

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the…

Information Theory · Computer Science 2013-03-01 Venkatesan Guruswami , Adam Smith

The security level of the achievability scheme for Wyner's wiretap channel model is examined from the perspective of the probability of correct decoding, $P_c$, at the wiretap channel decoder. In particular, for finite-alphabet memoryless…

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

A rateless code-i.e., a rate-compatible family of codes-has the property that codewords of the higher rate codes are prefixes of those of the lower rate ones. A perfect family of such codes is one in which each of the codes in the family is…

Information Theory · Computer Science 2011-06-07 Uri Erez , Mitchell D. Trott , Gregory W. Wornell

In this paper, we study the problem of relaying a single bit over a tandem of binary-input channels, with the goal of attaining the highest possible error exponent in the exponentially decaying error probability. Our previous work gave an…

Information Theory · Computer Science 2024-06-07 Yan Hao Ling , Jonathan Scarlett

Marton's optimal error exponent for the lossy source coding problem is defined as a non-convex optimization problem. This fact had prevented us to develop an efficient algorithm to compute it. This problem is caused by the fact that the…

Information Theory · Computer Science 2024-09-13 Yutaka Jitsumatsu

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 study the problem of channel resolvability for fixed i.i.d. input distributions and discrete memoryless channels (DMCs), and derive the strong converse theorem for any DMCs that are not necessarily full rank. We also derive the optimal…

Information Theory · Computer Science 2014-04-23 Shun Watanabe , Masahito Hayashi

This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

This paper presents a saddlepoint approximation of the random-coding union bound of Polyanskiy et al. for i.i.d. random coding over discrete memoryless channels. The approximation is single-letter, and can thus be computed efficiently.…

Information Theory · Computer Science 2014-04-28 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

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

It is well known that {\em superposition coding}, namely separately encoding the independent sources, is optimal for symmetric multilevel diversity coding (SMDC) (Yeung-Zhang 1999). However, the characterization of the coding rate region…

Information Theory · Computer Science 2019-05-22 Tao Guo , Raymond W. Yeung