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We derive upper and lower bounds for the error exponents of lossless streaming compression of two correlated sources under the blockwise and symbolwise settings. We consider the linear scaling regime in which the delay is a scalar multiple…

Information Theory · Computer Science 2016-02-24 Lin Zhou , Vincent Yan Fu Tan , Mehul Motani

A general method of coding over expansion is proposed,which allows one to reduce the highly non-trivial problems of coding over analog channels and compressing analog sources to a set of much simpler subproblems, coding over discrete…

Information Theory · Computer Science 2015-05-21 Hongbo Si , O. Ozan Koyluoglu , Kumar Appaiah , Sriram Vishwanath

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

We consider the problem of transmission of several distributed correlated sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel.…

Information Theory · Computer Science 2016-11-15 R. Rajesh , Vinod Sharma , V. K. Varshenya

We show that the probability distribution of the error exponent in i.i.d. code ensembles over classical-quantum (CQ) channels with arbitrary output states accumulates above a threshold that is strictly larger than the CQ random coding…

Information Theory · Computer Science 2025-07-10 Giuseppe Cocco , Javier Rodríguez Fonollosa

We provide a novel upper-bound on Witsenhausen's rate, the rate required in the zero-error analogue of the Slepian-Wolf problem; our bound is given in terms of a new information-theoretic functional defined on a certain graph. We then use…

Information Theory · Computer Science 2010-01-25 Benjamin G. Kelly , Aaron B. Wagner

This paper determines the range of feasible values of standard error exponents for binary-input memoryless symmetric channels of fixed capacity $C$ and shows that extremes are attained by the binary symmetric and the binary erasure channel.…

Information Theory · Computer Science 2012-12-06 Albert Guillen i Fabregas , Ingmar Land , Alfonso Martinez

Guruswami and Indyk showed in [1] that Forney's error exponent can be achieved with linear coding complexity over binary symmetric channels. This paper extends this conclusion to general discrete-time memoryless channels and shows that…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Jie Luo

We consider the problem of transmission of several distributed sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel. Sufficient…

Information Theory · Computer Science 2008-03-11 R. Rajesh , Vinod Sharma

The fundamental limit of Semantic Communications (joint source-channel coding) is established when the transmission needs to be kept covert from an external warden. We derive information-theoretic achievability and matching converse results…

Information Theory · Computer Science 2024-06-21 Abdelaziz Bounhar , Mireille Sarkiss , Michèle 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 consider the one helper source coding problem posed and investigated by Ahlswede, K\"orner and Wyner. In this system, the error probability of decoding goes to one as the source block length $n$ goes to infinity. This implies that we…

Information Theory · Computer Science 2019-01-18 Yasutada Oohama

We provide a tight asymptotic characterization of the error exponent for classical-quantum channel coding assisted by activated non-signaling correlations. Namely, we find that the optimal exponent--also called reliability function--is…

Quantum Physics · Physics 2024-10-08 Aadil Oufkir , Marco Tomamichel , Mario Berta

Bounds on the reliability function for the discrete memoryless relay channel are derived using the method of types. Two achievable error exponents are derived based on partial decode-forward and compress-forward which are well-known…

Information Theory · Computer Science 2016-11-17 Vincent Y. F. Tan

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

This paper investigates an information-theoretic model of secure semantic-aware communication. For this purpose, we consider the lossy joint source-channel coding (JSCC) of a memoryless semantic source transmitted over a memoryless wiretap…

Information Theory · Computer Science 2026-05-26 Denis Kozlov , Mahtab Mirmohseni , Rahim Tafazolli

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

In this work we investigate the behavior of the distortion threshold that can be guaranteed in joint source-channel coding, to within a prescribed excess-distortion probability. We show that the gap between this threshold and the optimal…

Information Theory · Computer Science 2011-12-08 Da Wang , Amir Ingber , Yuval Kochman

We consider the secret key generation problem when sources are randomly excited by the sender and there is a noiseless public discussion channel. Our setting is thus similar to recent works on channels with action-dependent states where the…

Information Theory · Computer Science 2016-11-15 Tzu-Han Chou , Vincent Y. F. Tan , Stark C. Draper

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes. However, this decomposition can fall…

Machine Learning · Computer Science 2019-05-15 Kristy Choi , Kedar Tatwawadi , Aditya Grover , Tsachy Weissman , Stefano Ermon