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Performance evaluation of particular channel coding has been a significant topic in coding theory, often involving the use of bounding techniques. This paper focuses on the new family of capacity-achieving codes, Spinal codes, to provide a…

Information Theory · Computer Science 2025-10-14 Aimin Li , Xiaomeng Chen , Shaohua Wu , Gary C. F. Lee , Sumei Sun

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

This paper presents an analysis of spinal codes, a class of rateless codes proposed recently. We prove that spinal codes achieve Shannon capacity for the binary symmetric channel (BSC) and the additive white Gaussian noise (AWGN) channel…

Information Theory · Computer Science 2012-06-05 Hari Balakrishnan , Peter Iannucci , Jonathan Perry , Devavrat Shah

Shannon's analysis of the fundamental capacity limits for memoryless communication channels has been refined over time. In this paper, the maximum volume $M_\avg^*(n,\epsilon)$ of length-$n$ codes subject to an average decoding error…

Information Theory · Computer Science 2016-12-28 Pierre Moulin

Spinal codes is a new family of capacity-achieving rateless codes that has been shown to achieve better rate performance compared to Raptor codes, Strider codes, and rateless Low-Density Parity-Check (LDPC) codes. This correspondence…

Information Theory · Computer Science 2025-10-14 Aimin Li , Shaohua Wu , Xiaomeng Chen , Sumei Sun

Reed-Muller codes were introduced in 1954, with a simple explicit construction based on polynomial evaluations, and have long been conjectured to achieve Shannon capacity on symmetric channels. Major progress was made towards a proof over…

Information Theory · Computer Science 2023-04-06 Emmanuel Abbe , Colin Sandon

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

This paper derives an improved sphere-packing (ISP) bound for finite-length codes whose transmission takes place over symmetric memoryless channels. We first review classical results, i.e., the 1959 sphere-packing (SP59) bound of Shannon…

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

This paper studies the third-order characteristic of nonsingular discrete memoryless channels and the Gaussian channel with a maximal-power constraint. The third-order term in our expansions employs a new quantity here called the channel…

Information Theory · Computer Science 2024-08-23 Recep Can Yavas , Victoria Kostina , Michelle Effros

We derive a new upper bound on the reliability function for channel coding over discrete memoryless channels. Our bounding technique relies on two main elements: (i) adding an auxiliary genie-receiver that reveals to the original receiver a…

Information Theory · Computer Science 2022-09-05 Anelia Somekh-Baruch

A new lower bound on the error probability of maximum likelihood decoding of a binary code on a binary symmetric channel was proved in Barg and McGregor (2004, cs.IT/0407011). It was observed in that paper that this bound leads to a new…

Information Theory · Computer Science 2007-07-13 Alexander Barg

For the discrete-time additive white generalized Gaussian noise channel with a generalized input power constraint, with the respective shape and power parameters >= 1, we derive an upper bound on the optimal block error exponent. Explicit…

Information Theory · Computer Science 2025-09-11 Sergey Tridenski , Anelia Somekh-Baruch

Starting from Shannon's celebrated 1948 channel coding theorem, we trace the evolution of channel coding from Hamming codes to capacity-approaching codes. We focus on the contributions that have led to the most significant improvements in…

Information Theory · Computer Science 2007-07-13 Daniel J. Costello , G. David Forney

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

This paper is concerned with bounds on the maximum-likelihood (ML) decoding error probability of Reed-Solomon (RS) codes over additive white Gaussian noise (AWGN) channels. To resolve the difficulty caused by the dependence of the Euclidean…

Information Theory · Computer Science 2014-01-22 Qiutao Zhuang , Xiao Ma , Aleksander Kavcic

Let $W$ be a binary-input memoryless symmetric (BMS) channel with Shannon capacity $I(W)$ and fix any $\alpha > 0$. We construct, for any sufficiently small $\delta > 0$, binary linear codes of block length $O(1/\delta^{2+\alpha})$ and rate…

Information Theory · Computer Science 2022-01-25 Venkatesan Guruswami , Andrii Riazanov , Min Ye

In this work, we obtain lower and upper bounds on the maximal transmission rate at a given codeword length $n$, average probability of error $\epsilon$ and power constraint $\bar{P}$, over a finite valued, block fading additive white…

Information Theory · Computer Science 2017-11-15 Deekshith P K , Vinod Sharma

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

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 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
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