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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

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

We introduce a new quantum decoder based on a variant of the pretty good measurement, but defined via an alternative matrix quotient. We use this decoder to show new lower bounds on the error exponent both in the one-shot and asymptotic…

Quantum Physics · Physics 2025-07-29 Salman Beigi , Marco Tomamichel

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

The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor decoding. It is well-known that maximum likelihood decoding coincides with nearest neighbor decoding with respect to the Hamming metric on…

Information Theory · Computer Science 2015-06-12 Marcelo Firer , Judy L. Walker

We show universally attainable exponents for the decoding error and the mutual information and universally attainable equivocation rates for the conditional entropy for the broadcast channels with confidential messages. The error exponents…

Information Theory · Computer Science 2011-10-04 Masahito Hayashi , Ryutaroh Matsumoto

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

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

The binary asymmetric channel is a model for practical communication systems where the error probabilities for symbol transitions $0\rightarrow 1$ and $1\rightarrow0$ differ substantially. In this paper, we introduce the notion of…

Information Theory · Computer Science 2026-04-10 Shukai Wang , Cuiling Fan , Chunming Tang , Zhengchun Zhou

Motivated by applications of rateless coding, decision feedback, and ARQ, we study the problem of universal decoding for unknown channels, in the presence of an erasure option. Specifically, we harness the competitive minimax methodology…

Information Theory · Computer Science 2007-07-13 Neri Merhav , Meir Feder

A universal decoding procedure is proposed for the intersymbol interference (ISI) Gaussian channels. The universality of the proposed decoder is in the sense of being independent of the various channel parameters, and at the same time,…

Information Theory · Computer Science 2014-03-18 Wasim Huleihel , Neri Merhav

When information is to be transmitted over an unknown, possibly unreliable channel, an erasure option at the decoder is desirable. Using constant-composition random codes, we propose a generalization of Csiszar and Korner's Maximum Mutual…

Information Theory · Computer Science 2016-11-17 Pierre Moulin

We consider the problem of block-coded communication, where in each block, the channel law belongs to one of two disjoint sets. The decoder is aimed to decode only messages that have undergone a channel from one of the sets, and thus has to…

Information Theory · Computer Science 2015-09-08 Nir Weinberger , Neri Merhav

We consider the problem of modulation and estimation of a random parameter $U$ to be conveyed across a discrete memoryless channel. Upper and lower bounds are derived for the best achievable exponential decay rate of a general moment of the…

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

The likelihood decoder is a stochastic decoder that selects the decoded message at random, using the posterior distribution of the true underlying message given the channel output. In this work, we study a generalized version of this…

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

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We determine the exact error and strong converse exponents of shared randomness-assisted channel simulation in worst case total-variation distance. Namely, we find that these exponents can be written as simple optimizations over the R\'enyi…

Information Theory · Computer Science 2024-10-10 Aadil Oufkir , Michael X. Cao , Hao-Chung Cheng , Mario Berta

In this paper, a streaming transmission setup is considered where an encoder observes a new message in the beginning of each block and a decoder sequentially decodes each message after a delay of $T$ blocks. In this streaming setup, the…

Information Theory · Computer Science 2016-04-26 Si-Hyeon Lee , Vincent Y. F. Tan , Ashish Khisti

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with…

Information Theory · Computer Science 2016-11-18 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

Here we write in a unified fashion (using "R(P, Q, D)") the random coding exponents in channel coding and lossy source coding. We derive their explicit forms and show, that, for a given random codebook distribution Q, the channel decoding…

Information Theory · Computer Science 2017-10-31 Sergey Tridenski , Ram Zamir