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The performance of maximum-likelihood (ML) decoded binary linear block codes over the AWGN channel is addressed via the tangential-sphere bound (TSB) and two of its recent improved versions. The paper is focused on the derivation of the…

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

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…

Information Theory · Computer Science 2007-07-13 M. Twitto , I. Sason , S. Shamai

New non-asymptotic random coding theorems (with error probability $\epsilon$ and finite block length $n$) based on Gallager parity check ensemble and Shannon random code ensemble with a fixed codeword type are established for discrete input…

Information Theory · Computer Science 2013-03-05 En-hui Yang , Jin Meng

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

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By…

Information Theory · Computer Science 2021-01-01 Xinchun Yu , Shuangqin Wei , Yuan Luo

We examine regular and irregular repeat-accumulate (RA) codes with repetition degrees which are all even. For these codes and with a particular choice of an interleaver, we give an upper bound on the decoding error probability of a…

Information Theory · Computer Science 2010-02-22 Idan Goldenberg , David Burshtein

This paper derives an improved sphere-packing (ISP) bound targeting codes of short to moderate block lengths. We first review the 1967 sphere-packing (SP67) bound for discrete memoryless channels, and a recent improvement by Valembois and…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

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

Topological quantum error-correcting codes are a promising candidate for building fault-tolerant quantum computers. Decoding topological codes optimally, however, is known to be a computationally hard problem. Various decoders have been…

Quantum Physics · Physics 2020-04-01 Milap Sheth , Sara Zafar Jafarzadeh , Vlad Gheorghiu

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

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

We consider the problem of optimally decoding a quantum error correction code -- that is to find the optimal recovery procedure given the outcomes of partial "check" measurements on the system. In general, this problem is NP-hard. However,…

Quantum Physics · Physics 2009-11-13 David Poulin

In this work, we consider efficient maximum-likelihood decoding of linear block codes for small-to-moderate block lengths. The presented approach is a branch-and-bound algorithm using the cutting-plane approach of Zhang and Siegel (IEEE…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Eirik Rosnes , Stefan Ruzika , Stefan Scholl

Spinal codes are a type of capacity-achieving rateless codes that have been proved to approach the Shannon capacity over the additive white Gaussian noise (AWGN) channel and the binary symmetric channel (BSC). In this paper, we aim to…

Information Theory · Computer Science 2022-04-05 Aimin Li , Shaohua Wu , Jian Jiao , Ning Zhang , Qinyu Zhang

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

Motivated by recommendation systems, we consider the problem of estimating block constant binary matrices (of size $m \times n$) from sparse and noisy observations. The observations are obtained from the underlying block constant matrix…

Information Theory · Computer Science 2009-01-14 S. T. Aditya , Onkar Dabeer , Bikash Kumar Dey

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 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

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

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