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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

In this paper, new techniques are presented to either simplify or improve most existing upper bounds on the maximum-likelihood (ML) decoding performance of the binary linear codes over additive white Gaussian noise (AWGN) channels. Firstly,…

Information Theory · Computer Science 2015-03-19 Xiao Ma , Jia Liu , Baoming Bai

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 paper, we first introduce the concept of elementary linear subspace, which has similar properties to those of a set of coordinates. We then use elementary linear subspaces to derive properties of maximum rank distance (MRD) codes…

Information Theory · Computer Science 2008-03-03 Maximilien Gadouleau , Zhiyuan Yan

This paper starts by considering the minimization of the Renyi divergence subject to a constraint on the total variation distance. Based on the solution of this optimization problem, the exact locus of the points $\bigl( D(Q\|P_1),…

Information Theory · Computer Science 2015-10-27 Igal Sason

We probabilistically analyze the performance of the arithmetic coding algorithm under a probability model for binary data in which a message is received by a coder from a source emitting independent equally distributed bits, with 1…

Data Structures and Algorithms · Computer Science 2025-02-18 Hosam M. Mahmoud , Hans J. Rivertz

The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially…

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

The decoding error probability of codes is studied as a function of their block length. It is shown that the existence of codes with a polynomially small decoding error probability implies the existence of codes with an exponentially small…

Information Theory · Computer Science 2007-07-13 Alexei Ashikhmin , Vitaly Skachek

We derive an upper bound on the reliability function of mismatched decoding for zero-rate codes. The bound is based on a result by Koml\'os that shows the existence of a subcode with certain symmetry properties. The bound is shown to…

Information Theory · Computer Science 2021-12-08 Marco Bondaschi , Albert Guillén i Fàbregas , Marco Dalai

In this paper, we present a novel way for solving the main problem of designing the capacity approaching irregular low-density parity-check (LDPC) code ensemble over binary erasure channel (BEC). The proposed method is much simpler, faster,…

Information Theory · Computer Science 2021-03-02 H. Tavakoli , M. Ahmadian Attari , M. R. Peyghami

This paper tackles two problems that fall under the study of coding for insertions and deletions. These problems are motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm,…

Information Theory · Computer Science 2025-06-23 Omer Sabary , Daniella Bar-Lev , Yotam Gershon , Alexander Yucovich , Eitan Yaakobi

This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error…

Information Theory · Computer Science 2007-07-13 I. Sason , I. Goldenberg

We study near optimal error correction codes for real-time communication. In our setup the encoder must operate on an incoming source stream in a sequential manner, and the decoder must reconstruct each source packet within a fixed playback…

Information Theory · Computer Science 2013-05-16 Ahmed Badr , Ashish Khisti , Wai-Tian Tan , John Apostolopoulos

It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minimum Euclidean distance between a codeword and the received channel output vector, is the maximum likelihood solution and hence…

Information Theory · Computer Science 2022-05-09 Yizhu Wang , Wenyi Zhang

In this work, we derive the random coding error exponent for the uplink phase of a two-way relay system where physical layer network coding (PNC) is employed. The error exponent is derived for the practical (yet sub-optimum) XOR channel…

Information Theory · Computer Science 2017-02-07 Shakeel Salamat Ullah , Gianluigi Liva , Soung Chang Liew

This paper studies several properties of channel codes that approach the fundamental limits of a given (discrete or Gaussian) memoryless channel with a non-vanishing probability of error. The output distribution induced by an…

Information Theory · Computer Science 2013-09-03 Yury Polyanskiy , Sergio Verdu

We study the channel coding problem when errors and uncertainty occur in the encoding process. For simplicity we assume the channel between the encoder and the decoder is perfect. Focusing on linear block codes, we model the encoding…

Information Theory · Computer Science 2013-05-17 Jad Hachem , I-Hsiang Wang , Christina Fragouli , Suhas Diggavi

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 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 the typical random code is defined as the asymptotic normalized expectation of the logarithm of the probability of error, as opposed to the traditional definition of the random coding exponent as the normalized…

Information Theory · Computer Science 2018-12-18 Neri Merhav