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Consider communication over the binary erasure channel BEC using random low-density parity-check codes with finite-blocklength n from `standard' ensembles. We show that large error events is conveniently described within a scaling theory,…

Information Theory · Computer Science 2007-07-13 Abdelaziz Amraoui , Andrea Montanari , Tom Richardson , Rudiger Urbanke

We derive bounds on the asymptotic density of parity-check matrices and the achievable rates of binary linear block codes transmitted over memoryless binary-input output-symmetric (MBIOS) channels. The lower bounds on the density of…

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

In this paper, we present new achievability bounds on the maximal achievable rate of variable-length stop-feedback (VLSF) codes operating over a binary erasure channel (BEC) at a fixed message size $M = 2^k$. We provide new bounds for VLSF…

Information Theory · Computer Science 2023-07-31 Hengjie Yang , Richard D. Wesel

The generalized Poor-Verdu error lower bound established in [1] for multihypothesis testing is studied in the classical channel coding context. It is proved that for any sequence of block codes sent over the memoryless binary symmetric…

Information Theory · Computer Science 2021-11-05 Ling-Hua Chang , Po-Ning Chen , Fady Alajaji , Yunghsiang S. Han

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

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 study error bounds for linear programming decoding of regular LDPC codes. For memoryless binary-input output-symmetric channels, we prove bounds on the word error probability that are inverse doubly-exponential in the girth of the factor…

Information Theory · Computer Science 2011-04-12 Nissim Halabi , Guy Even

Optimal coding over the additive white Gaussian noise channel under the peak energy constraint is studied when there is noisy feedback over an orthogonal additive white Gaussian noise channel. As shown by Pinsker, under the peak energy…

Information Theory · Computer Science 2011-08-19 Yu Xiang , Young-Han Kim

We consider a decoder with an erasure option and a variable size list decoder for channels with non-casual side information at the transmitter. First, universally achievable error exponents are offered for decoding with an erasure option…

Information Theory · Computer Science 2009-03-13 Erez Sabbag , Neri Merhav

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 revisits the Gaussian degraded relay channel, where the link that carries information from the source to the destination is a physically degraded version of the link that carries information from the source to the relay. The…

Information Theory · Computer Science 2016-10-19 Silas L. Fong , Vincent Y. F. Tan

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

Improved bounds on the blocklength required to communicate over binary-input channels using polar codes, below some given error probability, are derived. For that purpose, an improved bound on the number of non-polarizing channels is…

Information Theory · Computer Science 2013-07-23 Dina Goldin , David Burshtein

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 focus on the problem of modulating a parameter onto a power-limited signal transmitted over a discrete-time Gaussian channel and estimating this parameter at the receiver. Considering the well-known threshold effect in non-linear…

Information Theory · Computer Science 2018-02-15 Neri Merhav

Existing fixed-length feedback communication schemes are either specialized to particular channels (Schalkwijk--Kailath, Horstein), or apply to general channels but either have high coding complexity (block feedback schemes) or are…

Information Theory · Computer Science 2016-09-08 Cheuk Ting Li , Abbas El Gamal

Motivated by the significant performance gains which polar codes experience under successive cancellation list decoding, their scaling exponent is studied as a function of the list size. In particular, the error probability is fixed and the…

Information Theory · Computer Science 2014-09-23 Marco Mondelli , S. Hamed Hassani , Rüdiger Urbanke

A concatenated coding scheme over binary memoryless symmetric (BMS) channels using a polarization transformation followed by outer sub-codes is analyzed. Achievable error exponents and upper bounds on the error rate are derived. The first…

Information Theory · Computer Science 2017-10-24 Dina Goldin , David Burshtein

For discrete memoryless multiple-access channels, we propose a general definition of variable length codes with a measure of the transmission rates at the receiver side. This gives a receiver perspective on the multiple-access channel…

Information Theory · Computer Science 2011-02-28 Stephane Musy

The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than…

Information Theory · Computer Science 2020-01-13 Nicolas Charpenay , Maël Le Treust