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This paper considers error probabilities of random codes for memoryless channels in the fixed-rate regime. Random coding is a fundamental scheme to achieve the channel capacity and many studies have been conducted for the asymptotics of the…

Information Theory · Computer Science 2017-07-17 Junya Honda

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

Using tools developed in a recent work by Shen and the second author, in this paper we carry out an in-depth study on the average decoding error probability of the random matrix ensemble over the erasure channel under three decoding…

Information Theory · Computer Science 2024-04-23 Chin Hei Chan , Fang-Wei Fu , Maosheng Xiong

Motivated by applications of rateless coding, decision feedback, and ARQ, we study the problem of universal decoding for unknown channels, in the presence of an erasure option. Specifically, we harness the competitive minimax methodology…

Information Theory · Computer Science 2007-07-13 Neri Merhav , Meir Feder

Error probabilities of random codes for memoryless channels are considered in this paper. In the area of communication systems, admissible error probability is very small and it is sometimes more important to discuss the relative gap…

Information Theory · Computer Science 2015-06-11 Junya Honda

We consider hard-decision iterative decoders for product codes over the erasure channel, which employ repeated rounds of decoding rows and columns alternatingly. We derive the exact asymptotic probability of decoding failure as a function…

Information Theory · Computer Science 2007-07-16 Moshe Schwartz , Paul H. Siegel , Alexander Vardy

We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is…

Information Theory · Computer Science 2008-01-23 Ryuhei Mori , Kenta Kasai , Tomoharu Shibuya , Kohichi Sakaniwa

We consider a generalization of the discrete memoryless channel, in which the channel probability distribution is replaced by a uniform distribution over clouds of channel output sequences. For a random ensemble of such channels, we derive…

Information Theory · Computer Science 2022-09-22 Sergey Tridenski , Anelia Somekh-Baruch

We propose two types of universal codes that are suited to two asymptotic regimes when the output alphabet is possibly continuous. The first class has the property that the error probability decays exponentially fast and we identify an…

Information Theory · Computer Science 2024-09-10 Masahito Hayashi

We derive the optimum second-order coding rates, known as second-order capacities, for erasure and list decoding. For erasure decoding for discrete memoryless channels, we show that second-order capacity is $\sqrt{V}\Phi^{-1}(\epsilon_t)$…

Information Theory · Computer Science 2014-04-22 Vincent Y. F. Tan , Pierre Moulin

This paper studies the second-order asymptotics of the discrete memoryless multiple-access channel with degraded message sets. For a fixed average error probability $\epsilon\in(0,1)$ and an arbitrary point on the boundary of the capacity…

Information Theory · Computer Science 2015-04-15 Jonathan Scarlett , Vincent Y. F. Tan

This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to…

Information Theory · Computer Science 2022-03-16 Lan V. Truong , Giuseppe Cocco , Josep Font-Segura , Albert Guillén i Fàbregas

We consider a decoder with an erasure option and a variable size list decoder for channels with non-casual side information at the transmitter. First, universally achievable error exponents are offered for decoding with an erasure option…

Information Theory · Computer Science 2009-03-13 Erez Sabbag , Neri Merhav

We analyze the trade-off between the undetected error probability (i.e., the probability that the channel decoder outputs an erroneous message without detecting the error) and the total error probability in the short blocklength regime. We…

Information Theory · Computer Science 2025-03-05 Alexander Sauter , A. Oguz Kislal , Giuseppe Durisi , Gianluigi Liva , Balazs Matuz , Erik G. Ström

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

This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. The proposed method is applicable to various channels and ensembles. The focus is on both…

Information Theory · Computer Science 2022-03-01 Ralf R. Müller

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

We study channel simulation under common randomness assistance in the finite-blocklength regime and identify the smooth channel max-information as a linear program one-shot converse on the minimal simulation cost for fixed error tolerance.…

Information Theory · Computer Science 2024-10-10 Michael X. Cao , Navneeth Ramakrishnan , Mario Berta , Marco Tomamichel

We study the problem of communicating over a discrete memoryless two-way channel using non-adaptive schemes, under a zero probability of error criterion. We derive single-letter inner and outer bounds for the zero-error capacity region,…

Information Theory · Computer Science 2021-09-13 Yujie Gu , Ofer Shayevitz

The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than…

Information Theory · Computer Science 2020-01-13 Nicolas Charpenay , Maël Le Treust
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