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This paper considers the memoryless input-constrained binary erasure channel (BEC). The channel input constraint is the $(d,\infty)$-runlength limited (RLL) constraint, which mandates that any pair of successive $1$s in the input sequence…

Information Theory · Computer Science 2022-04-15 V. Arvind Rameshwar , Navin Kashyap

A pruned variant of polar coding is proposed for binary erasure channels. For sufficiently small $\varepsilon>0$, we construct a series of capacity achieving codes with block length $N=\varepsilon^{-5}$, code rate…

Information Theory · Computer Science 2020-12-14 Hsin-Po Wang , Iwan Duursma

We show that linear codes combined with rejection sampling can yield a capacity-achieving scheme for simulating additive exchangeable noise channels. Specifically, our scheme achieves an amount of communication within $\log e + 1$ bits from…

Information Theory · Computer Science 2026-01-21 Jianguo Zhao , Cheuk Ting Li

Consider a binary linear code of length $N$, minimum distance $d_{\text{min}}$, transmission over the binary erasure channel with parameter $0 < \epsilon < 1$ or the binary symmetric channel with parameter $0 < \epsilon < \frac12$, and…

Information Theory · Computer Science 2018-01-30 Hamed Hassani , Shrinivas Kudekar , Or Ordentlich , Yury Polyanskiy , Rüdiger Urbanke

This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the…

Information Theory · Computer Science 2014-02-05 Victoria Kostina , Sergio Verdú

Since the work of Polyanskiy, Poor and Verd\'u on the finite blocklength performance of capacity-achieving codes for discrete memoryless channels, many papers have attempted to find further results for more practically relevant channels.…

Information Theory · Computer Science 2024-07-15 Holger Boche , Andrea Grigorescu , Rafael F. Schaefer , H. Vincent Poor

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated to the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson…

Information Theory · Computer Science 2021-04-16 Niloufar Ahmadypour , Amin Gohari

This paper discusses a new channel model and code design for the reader-to-tag channel in near-field passive radio frequency identification (RFID) systems using inductive coupling as a power transfer mechanism. If the receiver…

Information Theory · Computer Science 2016-11-17 Ángela I. Barbero , Eirik Rosnes , Guang Yang , Øyvind Ytrehus

We consider channel coding for Gaussian channels with the recently introduced mean and variance cost constraints. Through matching converse and achievability bounds, we characterize the optimal first- and second-order performance. The main…

Information Theory · Computer Science 2025-09-15 Adeel Mahmood , Aaron B. Wagner

This work studies the problem of constructing capacity-achieving codes from an algorithmic perspective. Specifically, we prove that there exists a Turing machine which, given a discrete memoryless channel $p_{Y|X}$, a target rate $R$ less…

Information Theory · Computer Science 2025-11-06 Angelos Gkekas , Nikos A. Mitsiou , Ioannis Souldatos , George K. Karagiannidis

We prove that, for all binary-input symmetric memoryless channels, polar codes enable reliable communication at rates within $\epsilon > 0$ of the Shannon capacity with a block length, construction complexity, and decoding complexity all…

Information Theory · Computer Science 2013-11-19 Venkatesan Guruswami , Patrick Xia

We prove that for any additive noise channel over $\mathbb{F}_q$, there exist error-correcting codes approaching channel capacity encodable by arithmetic circuits (with weighted addition gates) over $\mathbb{F}_q$ of size $O(n)$ and depth…

Information Theory · Computer Science 2026-04-21 Yuan Li

We compare the performance of short-length linear binary codes on the binary erasure channel and the binary-input Gaussian channel. We use a universal decoder that can decode any linear binary block code: Gaussian-elimination based…

Information Theory · Computer Science 2016-11-09 J. Van Wonterghem , A. Alloum , J. J. Boutros , M. Moeneclaey

Explicit codes are constructed that achieve the diversity-multiplexing gain tradeoff of the cooperative-relay channel under the dynamic decode-and-forward protocol for any network size and for all numbers of transmit and receive antennas at…

Information Theory · Computer Science 2007-07-13 Petros Elia , P. Vijay Kumar

This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. The proposed method is applicable to various channels and ensembles. The focus is on both…

Information Theory · Computer Science 2022-03-01 Ralf R. Müller

Polar codes are constructed for arbitrary channels by imposing an arbitrary quasigroup structure on the input alphabet. Just as with "usual" polar codes, the block error probability under successive cancellation decoding is…

Information Theory · Computer Science 2016-06-16 Rajai Nasser , Emre Telatar

Low-capacity scenarios have become increasingly important in the technology of the Internet of Things (IoT) and the next generation of wireless networks. Such scenarios require efficient and reliable transmission over channels with an…

Information Theory · Computer Science 2023-02-07 Mohammad Fereydounian , Hamed Hassani , Mohammad Vahid Jamali , Hessam Mahdavifar

In the random deletion channel, each bit is deleted independently with probability $p$. For the random deletion channel, the existence of codes of rate $(1-p)/9$, and thus bounded away from $0$ for any $p < 1$, has been known. We give an…

Information Theory · Computer Science 2019-06-13 Venkatesan Guruswami , Ray Li

We consider rate R = k/n causal linear codes that map a sequence of k-dimensional binary vectors {b_t} to a sequence of n-dimensional binary vectors {c_t}, such that each c_t is a function of {b_1,b_2,...,b_t}. Such a code is called anytime…

Information Theory · Computer Science 2011-06-02 Ravi Teja Sukhavasi , Babak Hassibi

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph