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This paper tackles two problems that fall under the study of coding for insertions and deletions. These problems are motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm,…

Information Theory · Computer Science 2025-06-23 Omer Sabary , Daniella Bar-Lev , Yotam Gershon , Alexander Yucovich , Eitan Yaakobi

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 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

Over binary input channels, uniform distribution is a universal prior, in the sense that it allows to maximize the worst case mutual information over all binary input channels, ensuring at least 94.2% of the capacity. In this paper, we…

Information Theory · Computer Science 2010-04-28 Emmanuel Abbe , Rethnakaran Pulikkoonattu

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

We derive a single-letter upper bound to the mismatched-decoding capacity for discrete memoryless channels. The bound is expressed as the mutual information of a transformation of the channel, such that a maximum-likelihood decoding error…

Information Theory · Computer Science 2021-02-16 Ehsan Asadi Kangarshahi , Albert Guillén i Fàbregas

The problem of distributed testing against independence with variable-length coding is considered when the \emph{average} and not the \emph{maximum} communication load is constrained as in previous works. The paper characterizes the optimum…

Information Theory · Computer Science 2020-05-19 Sadaf Salehkalaibar , Michele Wigger

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 prove the Courtade-Kumar conjecture, for several classes of n-dimensional Boolean functions, for all $n \geq 2$ and for all values of the error probability of the binary symmetric channel, $0 \leq p \leq 1/2$. This conjecture states that…

Information Theory · Computer Science 2017-02-09 Septimia Sarbu

Estimating Mutual Information (MI), a key measure of dependence of random quantities without specific modelling assumptions, is a challenging problem in high dimensions. We propose a novel mutual information estimator based on parametrizing…

Machine Learning · Statistics 2025-10-24 Haoran Ni , Martin Lotz

The error probability of block codes sent under a non-uniform input distribution over the memoryless binary symmetric channel (BSC) and decoded via the maximum a posteriori (MAP) decoding rule is investigated. It is proved that the ratio of…

Information Theory · Computer Science 2023-05-10 Ling-Hua Chang , Po-Ning Chen , Fady Alajaji

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

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

This paper investigates achievable information rates and error exponents of mismatched decoding when the channel belongs to the class of channels that are close to the decoding metric in terms of relative entropy. For both discrete- and…

Information Theory · Computer Science 2025-05-28 Priyanka Patel , Francesc Molina , Albert Guillén i Fàbregas

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 consider a basic joint communication and sensing setup comprising a transmitter, a receiver and a sensor. The transmitter sends a codeword to the receiver through a discrete memoryless channel, and the receiver is interested in decoding…

Information Theory · Computer Science 2024-12-09 Han Wu , Hamdi Joudeh

This paper investigates the error probability of a stochastic decision and the way in which it differs from the error probability of an optimal decision, i.e., the maximum a posteriori decision. This paper calls attention to the fact that…

Information Theory · Computer Science 2017-05-01 Jun Muramatsu , Shigeki Miyake

We derive various error exponents for communication channels with random states, which are available non-causally at the encoder only. For both the finite-alphabet Gel'fand-Pinsker channel and its Gaussian counterpart, the dirty-paper…

Information Theory · Computer Science 2022-05-17 Ran Tamir , Neri Merhav

This paper studies the second-order asymptotics of coding rates for the discrete memoryless multiple-access channel with a fixed target error probability. Using constant-composition random coding, coded time-sharing, and a variant of…

Information Theory · Computer Science 2014-11-18 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

We consider the discrete memoryless asymmetric broadcast channels. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this exponent…

Information Theory · Computer Science 2020-08-11 Yasutada Oohama