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In this paper, we study the coding delay and the average coding delay of random linear network codes (dense codes) over line networks with deterministic regular and Poisson transmission schedules. We consider both lossless networks and…

Information Theory · Computer Science 2012-02-03 Anoosheh Heidarzadeh , Amir H. Banihashemi

We consider a variant of the channel simulation problem with a single input and multiple outputs, where Alice observes a probability distribution $P$ from a set of prescribed probability distributions $\mathbb{\mathcal{P}}$, and sends a…

Information Theory · Computer Science 2021-09-07 Chak Fung Choi , Cheuk Ting Li

A new algorithm for efficient exact maximum likelihood decoding of polar codes (which may be CRC augmented), transmitted over the binary erasure channel, is presented. The algorithm applies a matrix triangulation process on a sparse polar…

Information Theory · Computer Science 2021-06-29 Yonatan Urman , David Burshtein

Consider a binary word being transmitted through a communication channel that introduces deletable errors where each bit of the word is either retained, flipped, erased or deleted. The simplest code for correcting \emph{all} possible…

Information Theory · Computer Science 2018-05-03 Ghurumuruhan Ganesan

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

For memoryless channels with continuous input alphabets, deterministic identification (DI) typically exhibits a linearithmic ($n\log n$) message growth. However, the exact DI capacity has long remained open due to a persistent gap between…

Information Theory · Computer Science 2026-05-07 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

We consider the discrete memoryless degraded broadcast channels with feedback. 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…

Information Theory · Computer Science 2015-04-24 Yasutada Oohama

We analytically approximate the expected sum capacity loss between the optimal downlink precoding technique of dirty paper coding (DPC), and the sub-optimal technique of zero-forcing precoding, for multiuser channels. We also consider the…

Information Theory · Computer Science 2021-11-22 Harsh Tataria , Mansoor Shafi , Dino Pjanić

The per-sample zero-dispersion channel model of the optical fiber is considered. It is shown that capacity is uniquely achieved by an input probability distribution that has continuous uniform phase and discrete amplitude that takes on…

Information Theory · Computer Science 2018-09-25 Jihad Fahs , Aslan Tchamkerten , Mansoor I. Yousefi

For an arbitrary degree distribution pair (DDP), we construct a sequence of low-density parity-check (LDPC) code ensembles with girth growing logarithmically in block-length using Ramanujan graphs. When the DDP has minimum left degree at…

Information Theory · Computer Science 2016-11-17 Arunkumar Subramanian , Andrew Thangaraj , Matthieu Bloch , Steven W. McLaughlin

The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node's activations. The first loss term imposes a…

Information Theory · Computer Science 2022-08-12 Eliya Nachmani , Yair Be'ery

We consider the problem of optimal probing of states of a channel by transmitter and receiver for maximizing rate of reliable communication. The channel is discrete memoryless (DMC) with i.i.d. states. The encoder takes probing actions…

Information Theory · Computer Science 2016-11-15 Himanshu Asnani , Haim Permuter , Tsachy Weissman

This paper is concerned with the problem of error-free communication over the i.i.d. duplication channel which acts on a transmitted sequence $ x_1 \cdots x_n $ by inserting a random number of copies of each symbol $ x_i $ next to the…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević

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

We introduce the sum channel, a new channel model motivated by applications in distributed storage and DNA data storage. In the error-free case, it takes as input an $\ell$-row binary matrix and outputs an $(\ell+1)$-row matrix whose first…

Information Theory · Computer Science 2026-04-14 Lyan Abboud , Eitan Yaakobi

In this letter, we present a hybrid iterative decoder for non-binary low density parity check (LDPC) codes over binary erasure channel (BEC), based on which the recursion of the erasure probability is derived to design non-binary LDPC codes…

Signal Processing · Electrical Eng. & Systems 2020-03-04 Yang Yu , Wen Chen , Lili Wei

With steady progress in the development of quantum networks, the question on how to best provide end-to-end characterization of such networks (Quantum Network Tomography) is quickly becoming more pressing. Initial results demonstrated how…

Quantum Physics · Physics 2025-11-11 Jake Navas , Jaden Brewer , Jaime Diaz , Matheus Guedes de Andrade , Don Towsley , Inès Montaño

Motivated by communication channels in which the transmitted sequences are subject to random permutations, as well as by certain DNA storage systems, we study the error control problem in settings where the information is stored/transmitted…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Vincent Y. F. Tan

A permutation code is a nonlinear code whose codewords are permutation of a set of symbols. We consider the use of permutation code in the deletion channel, and consider the symbol-invariant error model, meaning that the values of the…

Information Theory · Computer Science 2024-11-14 Minhan Gao , Kenneth W. Shum

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang