English
Related papers

Related papers: The MMI Decoder is Asymptotically Optimal for the …

200 papers

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

This paper provides a dual domain derivation of the error exponent of maximum mutual information (MMI) decoding with constant composition codes, showing it coincides with that of maximum likelihood decoding for discrete memoryless channels.…

Information Theory · Computer Science 2025-07-25 AmirPouya Moeini , Albert Guillén i Fàbregas

We study the universal attainability of the expurgated error exponent for discrete memoryless channels (DMCs). While the random-coding exponent is known to be universally attainable via maximum mutual information (MMI) decoding for DMCs, it…

Information Theory · Computer Science 2026-03-03 Seyed AmirPouya Moeini , Marco Dalai , Albert Guillén i Fàbregas

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

We derive various error exponents in the bee identification problem under two different decoding rules. Under na\"ive decoding, which decodes each bee independently of the others, we analyze a general discrete memoryless channel and a…

Information Theory · Computer Science 2020-11-20 Ran Tamir , 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

Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed…

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

We consider ensembles of channel codes that are partitioned into bins, and focus on analysis of exact random coding error exponents associated with optimum decoding of the index of the bin to which the transmitted codeword belongs. Two main…

Information Theory · Computer Science 2016-11-18 Neri Merhav

Consider the following framework of universal decoding suggested in [MerhavUniversal]. Given a family of decoding metrics and random coding distribution (prior), a single, universal, decoder is optimal if for any possible channel the…

Information Theory · Computer Science 2014-04-29 Nir Elkayam , Meir Feder

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

This work contains two main contributions concerning the expurgation of hierarchical ensembles for the asymmetric broadcast channel. The first is an analysis of the optimal maximum likelihood (ML) decoders for the weak and strong user. Two…

Information Theory · Computer Science 2017-11-29 Ran Averbuch , Nir Weinberger , Neri Merhav

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

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

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

We define the error exponent of the typical random code as the long-block limit of the negative normalized expectation of the logarithm of the error probability of the random code, as opposed to the traditional random coding error exponent,…

Information Theory · Computer Science 2017-08-25 Neri Merhav

In this paper, we analyze the performance of space-time block codes which enable symbolwise maximum likelihood decoding. We derive an upper bound of maximum mutual information (MMI) on space-time block codes that enable symbolwise maximum…

Information Theory · Computer Science 2007-07-13 Kenji Tanaka , Ryutaroh Matsumoto , Tomohiko Uyematsu

We consider the topic of universal decoding with a decoder that does not have direct access to the codebook, but only to noisy versions of the various randomly generated codewords, a problem motivated by biometrical identification systems.…

Information Theory · Computer Science 2016-09-05 Neri Merhav

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

An erasure channel with a fixed alphabet size $q$, where $q \gg 1$, is studied. It is proved that over any erasure channel (with or without memory), Maximum Distance Separable (MDS) codes achieve the minimum probability of error (assuming…

Information Theory · Computer Science 2008-06-06 Shervan Fashandi , Shahab Oveis Gharan , Amir K. Khandani
‹ Prev 1 2 3 10 Next ›