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This paper shows the strong converse and the dispersion of memoryless channels with cost constraints and performs refined analysis of the third order term in the asymptotic expansion of the maximum achievable channel coding rate, showing…

Information Theory · Computer Science 2015-10-09 Victoria Kostina , Sergio Verdú

A key question for most applications involving reconfigurable linear wave systems is how accurately a desired linear operator can be realized by configuring the system's tunable elements. The relevance of this question spans from…

Signal Processing · Electrical Eng. & Systems 2026-02-17 Philipp del Hougne

We consider the problem of distributed binary hypothesis testing in a parallel network topology where sensors independently observe some phenomenon and send a finite rate summary of their observations to a fusion center for the final…

Information Theory · Computer Science 2016-06-29 Alla Tarighati , Joakim Jalden

This paper explores the possibilities and limitations of error correction by the structural simplicity of error mechanisms. Specifically, we consider channel models, called \emph{samplable additive channels}, in which (a) errors are…

Information Theory · Computer Science 2018-05-15 Kenji Yasunaga

We consider wiretap channels with uncertainty on the eavesdropper channel under (i) noisy blockwise type II, (ii) compound, or (iii) arbitrarily varying models. We present explicit wiretap codes that can handle these models in a unified…

Information Theory · Computer Science 2022-11-03 Remi A. Chou

We consider the discrete memoryless asymmetric 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…

Information Theory · Computer Science 2020-08-11 Yasutada Oohama

Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain…

Data Structures and Algorithms · Computer Science 2023-08-21 Arnab Bhattacharyya , Sutanu Gayen , Kuldeep S. Meel , Dimitrios Myrisiotis , A. Pavan , N. V. Vinodchandran

We investigate whether uncoded schemes are optimal for Gaussian sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian sources on a Gaussian broadcast channel where each…

Information Theory · Computer Science 2017-03-02 Chao Tian , Jun Chen , Suhas Diggavi , Shlomo Shamai

In this paper, we investigate the approximate consensus problem in highly dynamic networks in which topology may change continually and unpredictably. We prove that in both synchronous and partially synchronous systems, approximate…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-11-13 Bernadette Charron-Bost , Matthias Függer , Thomas Nowak

In the "correlated sampling" problem, two players are given probability distributions $P$ and $Q$, respectively, over the same finite set, with access to shared randomness. Without any communication, the two players are each required to…

Computational Complexity · Computer Science 2020-11-24 Mohammad Bavarian , Badih Ghazi , Elad Haramaty , Pritish Kamath , Ronald L. Rivest , Madhu Sudan

This paper addresses optimal decoding strategies in lossy compression where the assumed distribution for compressor design mismatches the actual (true) distribution of the source. This problem has immediate relevance in standardized…

Information Theory · Computer Science 2026-02-04 Saeed R. Khosravirad , Ahmed Alkhateeb , Ingrid van de Voorde

This paper considers the joint compression of a pair of correlated sources, where the encoder is allowed to access only one of the sources. The objective is to recover both sources under separate distortion constraints for each source while…

Information Theory · Computer Science 2024-11-07 Huiyuan Yang , Yuxuan Shi , Shuo Shao , Xiaojun Yuan

Under mild assumptions, we show the exact convergence rate in total variation is also exact in weaker Wasserstein distances for the Metropolis-Hastings independence sampler. We develop a new upper and lower bound on the worst-case…

Statistics Theory · Mathematics 2022-11-15 Austin Brown , Galin L. Jones

The common approach of designing a communication device is to maximize a well-defined objective function, e.g., the channel capacity and the cut-off rate. We propose easy-to-implement solutions for Gaussian channels that approximate the…

Information Theory · Computer Science 2016-03-24 Qian Yu

In the near future, the Internet of Things will interconnect billions of devices, forming a vast network where users sporadically transmit short messages through multi-path wireless channels. These channels are characterized by the…

Information Theory · Computer Science 2025-05-05 Sajad Daei , Saeed Razavikia , Mikael Skoglund , Gabor Fodor , Carlo Fischione

Determining the optimal fidelity for the transmission of quantum information over noisy quantum channels is one of the central problems in quantum information theory. Recently, [Berta-Borderi-Fawzi-Scholz, Mathematical Programming, 2021]…

Quantum Physics · Physics 2026-04-21 Yeow Meng Chee , Hoang Ta , Van Khu Vu

We consider the problem of encoding a deterministic source sequence (a.k.a.\ individual sequence) for the degraded wiretap channel by means of an encoder and decoder that can both be implemented as finite--state machines. Our first main…

Information Theory · Computer Science 2022-01-05 Neri Merhav

Tight bounds for several symmetric divergence measures are introduced, given in terms of the total variation distance. Each of these bounds is attained by a pair of 2 or 3-element probability distributions. An application of these bounds…

Information Theory · Computer Science 2016-11-15 Igal Sason

We prove tight upper and lower bounds on approximation ratios of all Boolean Max-2CSP problems in the streaming model. Specifically, for every type of Max-2CSP problem, we give an explicit constant $\alpha$, s.t. for any $\epsilon>0$ (i)…

Computational Complexity · Computer Science 2021-01-13 Chi-Ning Chou , Alexander Golovnev , Santhoshini Velusamy

Channel simulation is an alternative to quantization and entropy coding for performing lossy source coding. Recently, channel simulation has gained significant traction in both the machine learning and information theory communities, as it…

Information Theory · Computer Science 2026-02-10 Gergely Flamich , Sharang M. Sriramu , Aaron B. Wagner