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Guruswami and Indyk showed in [1] that Forney's error exponent can be achieved with linear coding complexity over binary symmetric channels. This paper extends this conclusion to general discrete-time memoryless channels and shows that…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Jie Luo

We revisit the derivation of expurgated error exponents using a method of type class enumeration, which is inspired by statistical-mechanical methods, and which has already been used in the derivation of random coding exponents in several…

Information Theory · Computer Science 2013-01-18 Neri Merhav

Consider the transmission of a polar code of block length $N$ and rate $R$ over a binary memoryless symmetric channel $W$ and let $P_e$ be the block error probability under successive cancellation decoding. In this paper, we develop new…

Information Theory · Computer Science 2016-08-05 Marco Mondelli , S. Hamed Hassani , Rüdiger Urbanke

Algorithms based on multiple decoding attempts of Reed-Solomon (RS) codes have recently attracted new attention. Choosing decoding candidates based on rate-distortion (R-D) theory, as proposed previously by the authors, currently provides…

Information Theory · Computer Science 2016-11-17 Phong S. Nguyen , Henry D. Pfister , Krishna R. Narayanan

In 1973, Gallager proved that the random-coding bound is exponentially tight for the random code ensemble at all rates, even below expurgation. This result explained that the random-coding exponent does not achieve the expurgation exponent…

Information Theory · Computer Science 2013-08-29 Yuval Domb , Ram Zamir , Meir Feder

Deep generative models are routinely used in generating samples from complex, high-dimensional distributions. Despite their apparent successes, their statistical properties are not well understood. A common assumption is that with enough…

Machine Learning · Statistics 2025-01-15 Edric Tam , David B. Dunson

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

An upper bound on the error probability of specific lattices, based on their distance-spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers.…

Information Theory · Computer Science 2013-01-03 Yuval Domb , Meir Feder

Analytic combinatorics in several variables refers to a suite of tools that provide sharp asymptotic estimates for certain combinatorial quantities. In this paper, we apply these tools to determine the Gilbert--Varshamov lower bound on the…

Information Theory · Computer Science 2024-12-30 Keshav Goyal , Duc Tu Dao , Mladen Kovačević , Han Mao Kiah

We study properties of rank metric and codes in rank metric over finite fields. We show that in rank metric perfect codes do not exist. We derive an existence bound that is the equivalent of the Gilbert--Varshamov bound in Hamming metric.…

Discrete Mathematics · Computer Science 2007-07-13 P. Loidreau

This paper is about deriving lower bounds on the error exponents for the two-user interference channel under the random coding regime for several ensembles. Specifically, we first analyze the standard random coding ensemble, where the…

Information Theory · Computer Science 2017-06-22 Wasim Huleihel , Neri Merhav

Universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC's)), and various ensembles of random codes, are studied by combining the competitive minimax approach,…

Information Theory · Computer Science 2007-08-01 Yaniv Akirav , Neri Merhav

The use of multiple antenna arrays in transmission and reception has become an integral part of modern wireless communications. To quantify the performance of such systems, the evaluation of bounds on the error probability of realistic…

Information Theory · Computer Science 2017-11-28 Apostolos Karadimitrakis , Aris L. Moustakas , Romain Couillet

Randomized singular value decomposition (RSVD) is a class of computationally efficient algorithms for computing the truncated SVD of large data matrices. Given an $m \times n$ matrix $\widehat{{\mathbf M}}$, the prototypical RSVD algorithm…

Statistics Theory · Mathematics 2025-05-27 Yichi Zhang , Minh Tang

We examine regular and irregular repeat-accumulate (RA) codes with repetition degrees which are all even. For these codes and with a particular choice of an interleaver, we give an upper bound on the decoding error probability of a…

Information Theory · Computer Science 2010-02-22 Idan Goldenberg , David Burshtein

We consider a channel-independent decoder which is for i.i.d. random codes what the maximum mutual-information decoder is for constant composition codes. We show that this decoder results in exactly the same i.i.d. random coding error…

Information Theory · Computer Science 2018-11-06 Sergey Tridenski , Ram Zamir

We consider the problem of jointly optimum modulation and estimation of a real-valued random parameter, conveyed over an additive white Gaussian noise (AWGN) channel, where the performance metric is the large deviations behavior of the…

Information Theory · Computer Science 2016-11-17 Neri Merhav

In this paper, we first introduce the concept of elementary linear subspace, which has similar properties to those of a set of coordinates. Using this new concept, we derive properties of maximum rank distance (MRD) codes that parallel…

Information Theory · Computer Science 2007-07-13 Maximilien Gadouleau , Zhiyuan Yan

We consider the discrete memoryless degraded broadcast channels. 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 exponent function.…

Information Theory · Computer Science 2015-04-23 Yasutada Oohama

Here we write in a unified fashion (using "R(P, Q, D)") the random coding exponents in channel coding and lossy source coding. We derive their explicit forms and show, that, for a given random codebook distribution Q, the channel decoding…

Information Theory · Computer Science 2017-10-31 Sergey Tridenski , Ram Zamir