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We address the problem of bounding below the probability of error under maximum likelihood decoding of a binary code with a known distance distribution used on a binary symmetric channel. An improved upper bound is given for the maximum…

Information Theory · Computer Science 2007-07-16 Alexander Barg , Andrew McGregor

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 Igal Sason , Idan Goldenberg

When information is to be transmitted over an unknown, possibly unreliable channel, an erasure option at the decoder is desirable. Using constant-composition random codes, we propose a generalization of Csiszar and Korner's Maximum Mutual…

Information Theory · Computer Science 2016-11-17 Pierre Moulin

Polar codes are a family of capacity-achieving codes that have explicit and low-complexity construction, encoding, and decoding algorithms. Decoding of polar codes is based on the successive-cancellation decoder, which decodes in a bit-…

Information Theory · Computer Science 2018-03-06 Boaz Shuval , Ido Tal

We discuss and analyze a list-message-passing decoder with verification for low-density parity-check (LDPC) codes on the q-ary symmetric channel (q-SC). Rather than passing messages consisting of symbol probabilities, this decoder passes…

Information Theory · Computer Science 2015-03-13 Fan Zhang , Henry D. Pfister

In this paper, we present a novel communication channel, called the absorption channel, inspired by information transmission in neurons. Our motivation comes from in-vivo nano-machines, emerging medical applications, and brain-machine…

Information Theory · Computer Science 2023-02-21 Zuo Ye , Ohad Elishco

We consider a molecular channel, in which messages are encoded to the frequency of objects in a pool, and whose output during reading time is a noisy version of the input frequencies, as obtained by sampling with replacement from the pool.…

Information Theory · Computer Science 2025-04-28 Ran Tamir , Nir Weinberger

A novel and efficient neural decoder algorithm is proposed. The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group. By combining neural belief propagation with permutations from the Automorphism…

Information Theory · Computer Science 2018-01-10 Eliya Nachmani , Yaron Bachar , Elad Marciano , David Burshtein , Yair Be'ery

Decoding sits between a language model and everything we do with it, yet it is still treated as a heuristic knob-tuning exercise. We argue decoding should be understood as a principled optimisation layer: at each token, we solve a…

Machine Learning · Computer Science 2026-02-26 Xiaotong Ji , Rasul Tutunov , Matthieu Zimmer , Haitham Bou-Ammar

The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay…

Information Theory · Computer Science 2012-03-29 Erik Johannesson , Anders Rantzer , Bo Bernhardsson , Andrey Ghulchak

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

We present many new results related to reliable (interactive) communication over insertion-deletion channels. Synchronization errors, such as insertions and deletions, strictly generalize the usual symbol corruption errors and are much…

Information Theory · Computer Science 2018-03-22 Bernhard Haeupler , Amirbehshad Shahrasbi , Ellen Vitercik

In this paper, we focus on the demodulation/decoding of the complex modulations/codes that approach the Shannon capacity. Theoretically, the maximum likelihood (ML) algorithm can achieve the optimal error performance whereas it has…

Information Theory · Computer Science 2022-06-14 Boxiang He , Zitao Wu , Fanggang Wang

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector…

Information Theory · Computer Science 2009-11-13 Tadashi Wadayama

Recent work have shown that Reed-Muller (RM) codes achieve the erasure channel capacity. However, this performance is obtained with maximum-likelihood decoding which can be costly for practical applications. In this paper, we propose an…

Information Theory · Computer Science 2016-01-27 Alexandre Soro , Jerome Lacan , Vincent Roca , Valentin Savin , Mathieu Cunche

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

We consider a relay channel for which the following assumptions are made. (1) The source-destination and relay-destination channels are orthogonal (frequency division relay channel). (2) The relay implements the decode-and-forward protocol.…

Information Theory · Computer Science 2009-02-17 Brice Djeumou , Samson Lasaulce , Antoine Berthet

The problem of designing codes for deletion-correction and synchronization has received renewed interest due to applications in DNA-based data storage systems that use nanopore sequencers as readout platforms. In almost all instances,…

Information Theory · Computer Science 2026-05-26 Yuan-Pon Chen , Olgica Milenkovic , João Ribeiro , Jin Sima

Learning, prediction, and compression are intimately connected: a model that accurately predicts the next symbol in a sequence can be coupled with a source coder to compress that sequence near its information-theoretic limit. When tokenized…

Information Theory · Computer Science 2026-05-05 Vishnu Teja Kunde , Jean-Francois Chamberland , Krishna R. Narayanan , Jamison Ebert

This paper considers the average complexity of maximum likelihood (ML) decoding of convolutional codes. ML decoding can be modeled as finding the most probable path taken through a Markov graph. Integrated with the Viterbi algorithm (VA),…

Information Theory · Computer Science 2016-11-17 Jie Luo
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