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Motivated by applications of biometric identification and content identification systems, we consider the problem of random coding for channels, where each codeword undergoes lossy compression (vector quantization), and where the decoder…

Information Theory · Computer Science 2016-09-29 Neri Merhav

For the model of communication through a discrete memoryless channel using i.i.d. random block codes, where the channel is changing slowly from block to block, we propose a stochastic algorithm for adaptation of the generating distribution…

Information Theory · Computer Science 2018-01-23 Sergey Tridenski , Ram Zamir

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

For a discrete memoryless channel with finite input and output alphabets, we prove convergence of a parametric family of iterative computations of the optimal correct-decoding exponent. The exponent, as a function of communication rate, is…

Information Theory · Computer Science 2020-05-18 Sergey Tridenski , Anelia Somekh-Baruch , Ram Zamir

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 studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred to as classes), and codewords are independently generated according to a distribution…

Information Theory · Computer Science 2014-02-19 Adrià Tauste Campo , Gonzalo Vazquez-Vilar , Albert Guillén i Fàbregas , Tobias Koch , Alfonso Martinez

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 universal decoding for arbitrary unknown channels in the random coding regime. For a given random coding distribution and a given class of metric decoders, we propose a generic universal decoder whose average…

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

The error exponent of fixed-length lossy source coding was established by Marton. Ahlswede showed that this exponent can be discontinuous at a rate $R$, depending on the probability distribution $P$ of the given information source and the…

Information Theory · Computer Science 2023-04-25 Yutaka Jitsumatsu

We study the problem of generating an approximately i.i.d. string at the output of a discrete memoryless channel using a limited amount of randomness at its input in presence of causal noiseless feedback. Feedback does not decrease the…

Information Theory · Computer Science 2016-09-29 Mani Bastani Parizi , Emre Telatar

This paper proposes a method to optimize communication code rates via the application of neural polar decoders (NPDs). Employing this approach enables simultaneous optimization of code rates over input distributions while providing a…

Information Theory · Computer Science 2025-06-23 Ziv Aharoni , Bashar Huleihel , Henry D Pfister , Haim H Permuter

This work contains two main contributions concerning the asymmetric broadcast channel. The first is an analysis of the exact random coding error exponents for both users, and the second is the derivation of universal decoders for both…

Information Theory · Computer Science 2017-02-28 Ran Averbuch , Neri Merhav

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

Consider the asymmetric broadcast channel with a random superposition codebook, which may be comprised of constant composition or \iid codewords. By applying Forney's optimal decoder for individual messages and the message pair for the…

Information Theory · Computer Science 2019-06-10 Daming Cao , Vincent Y. F. Tan

The form of Dueck and K\"orner's exponent function for correct decoding probability for discrete memoryless channels at rates above the capacity is similar to the form of Csisz\'ar and K\"orner's exponent function for correct decoding…

Information Theory · Computer Science 2016-05-30 Yutaka Jitsumatsu , Yasutada Oohama

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

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

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 expurgated exponents for joint source-channel coding of discrete memoryless sources and channels under i.i.d. random coding. We show that a two-class partitioning of source sequences, where the codeword distribution…

Information Theory · Computer Science 2026-01-22 Seyed AmirPouya Moeini , Albert Guillén i Fàbregas

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
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