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We introduce an expurgation method for source coding with side information that enables direct dual-domain derivations of expurgated error exponents. Dual-domain methods yield optimization problems over few parameters, with any sub-optimal…

Information Theory · Computer Science 2026-02-25 Mehdi Dabirnia , Hamdi Joudeh , Albert Guillén i Fàbregas

The error exponent in lossy source coding characterizes the asymptotic decay rate of error probability with respect to blocklength. The Marton's error exponent provides the theoretically optimal bound on this rate. However, computation…

Information Theory · Computer Science 2025-07-29 Jiachuan Ye , Shitong Wu , Lingyi Chen , Wenyi Zhang , Huihui Wu , Hao Wu

This paper studies expurgated error exponents for joint source-channel coding for discrete memoryless sources and channels. We consider a partition of the source messages into classes, where the codeword distributions depend on the class.…

Information Theory · Computer Science 2025-09-16 AmirPouya Moeini , 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

We study a class of $K$-encoder hypothesis testing against conditional independence problems. Under the criterion that stipulates minimization of the Type II error subject to a (constant) upper bound $\epsilon$ on the Type I error, we…

Information Theory · Computer Science 2022-07-05 Abdellatif Zaidi

This paper studies the performance of sparse regression codes for lossy compression with the squared-error distortion criterion. In a sparse regression code, codewords are linear combinations of subsets of columns of a design matrix. It is…

Information Theory · Computer Science 2017-07-17 Ramji Venkataramanan , Sekhar Tatikonda

The exact order of the optimal sub-exponentially decaying factor in the classical bounds on the error probability of fixed-length codes over a Gallager-symmetric discrete memoryless channel with and without ideal feedback is determined.…

Information Theory · Computer Science 2019-09-02 Yücel Altuğ , Aaron B. Wagner

Csisz\'ar's channel coding theorem for multiple codebooks is generalized allowing the codeword lenghts differ across codebooks. Also in this case, for each codebook an error exponent can be achieved that equals the random coding exponent…

Information Theory · Computer Science 2017-01-24 Lóránt Farkas , Tamás Kói

In this paper, random coding error exponents and cutoff rate are studied for noncoherent Rician fading channels, where neither the receiver nor the transmitter has channel side information. First, it is assumed that the input is subject…

Information Theory · Computer Science 2016-11-18 Mustafa Cenk Gursoy

We propose a source/channel duality in the exponential regime, where success/failure in source coding parallels error/correctness in channel coding, and a distortion constraint becomes a log-likelihood ratio (LLR) threshold. We establish…

Information Theory · Computer Science 2017-01-27 Sergey Tridenski , Ram Zamir

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

In this paper we consider a Metzner-Kapturowski-like decoding algorithm for high-order interleaved sum-rank-metric codes, offering a novel perspective on the decoding process through the concept of an error code. The error code, defined as…

Information Theory · Computer Science 2024-09-30 Thomas Jerkovits , Felicitas Hörmann , Hannes Bartz

We consider the discrete memoryless degraded broadcast channels with feedback. 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…

Information Theory · Computer Science 2015-04-24 Yasutada Oohama

In the theory of lossy compression, the rate-distortion (R-D) function $R(D)$ describes how much a data source can be compressed (in bit-rate) at any given level of fidelity (distortion). Obtaining $R(D)$ for a given data source establishes…

Information Theory · Computer Science 2023-10-31 Yibo Yang , Stephan Eckstein , Marcel Nutz , Stephan Mandt

In continuation to an earlier work, where error exponents of typical random codes were studied in the context of general block coding, with no underlying structure, here we carry out a parallel study on typical random, time-varying trellis…

Information Theory · Computer Science 2019-03-05 Neri Merhav

Consider the transmission of a polar code of block length $N$ and rate $R$ over a binary memoryless symmetric channel $W$ and let $P_e$ be the block error probability under successive cancellation decoding. In this paper, we develop new…

Information Theory · Computer Science 2016-08-05 Marco Mondelli , S. Hamed Hassani , Rüdiger Urbanke

We consider the additive white Gaussian noise channels. We prove that the error probability of decoding tends to one exponentially for rates above the capacity and derive the optimal exponent function. We shall demonstrate that the…

Information Theory · Computer Science 2017-02-07 Yasutada Oohama

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

We consider a Shannon cipher system for memoryless sources, in which distortion is allowed at the legitimate decoder. The source is compressed using a rate distortion code secured by a shared key, which satisfies a constraint on the…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav

We consider the problem of erasure/list decoding using certain classes of simplified decoders. Specifically, we assume a class of erasure/list decoders, such that a codeword is in the list if its likelihood is larger than a threshold. This…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav