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This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the…

Information Theory · Computer Science 2014-10-13 Sy-Quoc Le , Vincent Y. F. Tan , Mehul Motani

Second order asymptotics of fixed-length source coding and intrinsic randomness is discussed with a constant error constraint. There was a difference between optimal rates of fixed-length source coding and intrinsic randomness, which never…

Information Theory · Computer Science 2010-01-23 Masahito Hayashi

This paper studies the second-order asymptotics of the discrete memoryless multiple-access channel with degraded message sets. For a fixed average error probability $\epsilon\in(0,1)$ and an arbitrary point on the boundary of the capacity…

Information Theory · Computer Science 2015-04-15 Jonathan Scarlett , Vincent Y. F. Tan

We study the discrete-time Poisson channel under the constraint that its average input power (in photons per channel use) must not exceed some constant E. We consider the wideband, high-photon-efficiency extreme where E approaches zero, and…

Information Theory · Computer Science 2014-04-25 Ligong Wang , Gregory W. Wornell

We present novel non-asymptotic or finite blocklength achievability bounds for three side-information problems in network information theory. These include (i) the Wyner-Ahlswede-Korner (WAK) problem of almost-lossless source coding with…

Information Theory · Computer Science 2014-12-30 Shun Watanabe , Shigeaki Kuzuoka , Vincent Y. F. Tan

This paper shows that the capacity region of the continuous-time Poisson broadcast channel is achieved via superposition coding for most channel parameter values. Interestingly, the channel in some subset of these parameter values does not…

Information Theory · Computer Science 2015-08-28 Hyeji Kim , Benjamin Nachman , Abbas El Gamal

We study the problem of channel resolvability for fixed i.i.d. input distributions and discrete memoryless channels (DMCs), and derive the strong converse theorem for any DMCs that are not necessarily full rank. We also derive the optimal…

Information Theory · Computer Science 2014-04-23 Shun Watanabe , Masahito Hayashi

New non-asymptotic random coding theorems (with error probability $\epsilon$ and finite block length $n$) based on Gallager parity check ensemble and Shannon random code ensemble with a fixed codeword type are established for discrete input…

Information Theory · Computer Science 2013-03-05 En-hui Yang , Jin Meng

The noisy permutation channel is a useful abstraction introduced by Makur for point-to-point communication networks and biological storage. While the asymptotic capacity results exist for this model, the characterization of the second-order…

Information Theory · Computer Science 2024-06-24 Lugaoze Feng , Baoji Wang , Guocheng Lv , Xvnan Li , Luhua Wang , Ye jin

This paper investigates the maximal channel coding rate achievable at a given blocklength $n$ and error probability $\epsilon$, when the codewords are subject to a long-term (i.e., averaged-over-all-codeword) power constraint. The…

Information Theory · Computer Science 2015-07-15 Wei Yang , Giuseppe Caire , Giuseppe Durisi , Yury Polyanskiy

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

We propose an iterative method for approximately computing the capacity of discrete memoryless channels, possibly under additional constraints on the input distribution. Based on duality of convex programming, we derive explicit upper and…

Information Theory · Computer Science 2015-04-06 Tobias Sutter , David Sutter , Peyman Mohajerin Esfahani , John Lygeros

New capacity upper bounds are presented for the discrete-time Poisson channel with no dark current and an average-power constraint. These bounds are a simple consequence of techniques developed for the seemingly unrelated problem of upper…

Information Theory · Computer Science 2018-07-23 Mahdi Cheraghchi , João Ribeiro

The problem of determining the best achievable performance of arbitrary lossless compression algorithms is examined, when correlated side information is available at both the encoder and decoder. For arbitrary source-side information pairs,…

Information Theory · Computer Science 2020-07-15 Lampros Gavalakis , Ioannis Kontoyiannis

We derive improved and easily computable upper bounds on the capacity of the discrete-time Poisson channel under an average-power constraint and an arbitrary constant dark current term. This is accomplished by combining a general convex…

Information Theory · Computer Science 2020-11-03 Mahdi Cheraghchi , João Ribeiro

This paper presents a new derivation method of converse bounds on the non-asymptotic achievable rate of discrete weakly symmetric memoryless channels. It is based on the finite blocklength statistics of the channel, where with the use of an…

Information Theory · Computer Science 2022-02-08 Ioannis Papoutsidakis , Robert J. Piechocki , Angela Doufexi

The Poltyrev bound provides a very tight upper bound on the decoding error probability when using binary linear codes for transmission over the binary symmetric channel and the additive white Gaussian noise channel, making use of the code's…

Information Theory · Computer Science 2025-01-23 Tal Philosof , Ariel Doubchak , Amit Berman , Uri Erez

We develop bounds on the capacity of Poisson-repeat channels (PRCs) for which each input bit is independently repeated according to a Poisson distribution. The upper bounds are obtained by considering an auxiliary channel where the output…

Information Theory · Computer Science 2024-10-04 Mohammad Kazemi , Tolga M. Duman

We study variable-length feedback (VLF) codes with noiseless feedback for discrete memoryless channels. We present a novel non-asymptotic bound, which analyzes the average error probability and average decoding time of our modified…

Information Theory · Computer Science 2025-02-12 Recep Can Yavas , Vincent Y. F. Tan

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas