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相关论文: Expurgated Bounds for the Asymmetric Broadcast Cha…

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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…

信息论 · 计算机科学 2017-02-28 Ran Averbuch , Neri Merhav

A lower bound on the maximum likelihood (ML) decoding error exponent of linear block code ensembles, on the erasure channel, is developed. The lower bound turns to be positive, over an ensemble specific interval of erasure probabilities,…

信息论 · 计算机科学 2019-01-23 Enrico Paolini , Gianluigi Liva

A unified framework to obtain all known lower bounds (random coding, typical random coding and expurgated bound) on the reliability function of a point-to-point discrete memoryless channel (DMC) is presented. By using a similar idea for a…

信息论 · 计算机科学 2010-10-08 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

This paper studies expurgated random-coding bounds and exponents for channel coding with a given (possibly suboptimal) decoding rule. Variations of Gallager's analysis are presented, yielding several asymptotic and non-asymptotic bounds on…

信息论 · 计算机科学 2016-11-17 Jonathan Scarlett , Li Peng , Neri Merhav , Alfonso Martinez , Albert Guillén i Fàbregas

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…

信息论 · 计算机科学 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…

信息论 · 计算机科学 2016-11-17 Neri Merhav

We revisit the derivation of expurgated error exponents using a method of type class enumeration, which is inspired by statistical-mechanical methods, and which has already been used in the derivation of random coding exponents in several…

信息论 · 计算机科学 2013-01-18 Neri Merhav

We consider a broadcast channel with a degraded message set, in which a single transmitter sends a common message to two receivers and a private message to one of the receivers only. The main goal of this work is to find new lower bounds to…

信息论 · 计算机科学 2009-06-09 Yonatan Kaspi , Neri Merhav

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…

信息论 · 计算机科学 2019-06-10 Daming Cao , Vincent Y. F. Tan

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…

信息论 · 计算机科学 2020-11-20 Ran Tamir , Neri Merhav

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with…

信息论 · 计算机科学 2016-11-18 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

In this work we show how an improved lower bound to the error exponent of the memoryless multiple-access (MAC) channel is attained via the use of linear codes, thus demonstrating that structure can be beneficial even in cases where there is…

信息论 · 计算机科学 2016-11-18 Eli Haim , Yuval Kochman , Uri Erez

The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid…

信息论 · 计算机科学 2007-07-13 M. Twitto , I. Sason , S. Shamai

In this work, a new upper bound for average error probability of a two-user discrete memoryless (DM) multiple-access channel (MAC) is derived. This bound can be universally obtained for all discrete memoryless MACs with given input and…

信息论 · 计算机科学 2009-01-09 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

The performance of maximum-likelihood (ML) decoding on the binary erasure channel for finite-length low-density parity-check (LDPC) codes from two random ensembles is studied. The theoretical average spectrum of the Gallager ensemble is…

信息论 · 计算机科学 2018-11-21 Irina E. Bocharova , Boris D. Kudryashov , Vitaly Skachek , Eirik Rosnes , Øyvind Ytrehus

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…

信息论 · 计算机科学 2026-03-03 Seyed AmirPouya Moeini , Marco Dalai , Albert Guillén i Fàbregas

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…

信息论 · 计算机科学 2020-07-27 Ran Tamir , Neri Merhav

We investigate threshold-based multi-trial decoding of concatenated codes with an inner Maximum-Likelihood decoder and an outer error/erasure (L+1)/L-extended Bounded Distance decoder, i.e. a decoder which corrects e errors and t erasures…

信息论 · 计算机科学 2012-02-07 Christian Senger , Vladimir R. Sidorenko , Martin Bossert , Victor V. Zyablov

This paper is about deriving lower bounds on the error exponents for the two-user interference channel under the random coding regime for several ensembles. Specifically, we first analyze the standard random coding ensemble, where the…

信息论 · 计算机科学 2017-06-22 Wasim Huleihel , Neri Merhav

A Lagrange-dual (Gallager-style) lower bound is derived for the error exponent function of the typical random code (TRC) pertaining to the i.i.d. random coding ensemble and mismatched stochastic likelihood decoding. While the original…

信息论 · 计算机科学 2019-08-13 Neri Merhav
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