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A formula is derived for the capacity of the Gaussian channel with a benevolent message-cognizant rate-limited helper that provides a noncausal description of the noise to the encoder and decoder. This capacity is strictly larger than when…

Information Theory · Computer Science 2023-10-25 Amos Lapidoth , Ligong Wang , Yiming Yan

In this note we study Shannon capacity of channels in the context of classical Ramsey numbers. We overview some of the results on capacity of noisy channels modelled by graphs, and how some constructions may contribute to our knowledge of…

Combinatorics · Mathematics 2014-05-30 Xiaodong Xu , Stanisław Radziszowski

Channel capacity bounds are derived for a point-to-point indoor visible light communications (VLC) system with signal-dependent Gaussian noise. Considering both illumination and communication, the non-negative input of VLC is constrained by…

Information Theory · Computer Science 2020-11-03 Jin-Yuan Wang , Xian-Tao Fu , Rong-Rong Lu , Jun-Bo Wang , Min Lin , Julian Cheng

For a continuous-input-continuous-output arbitrarily distributed quantum channel carrying classical information, the channel capacity can be computed in terms of the distribution of the channel envelope, received signal strength over a…

Information Theory · Computer Science 2022-06-09 Mouli Chakraborty , Harun Siljak , Indrakshi Dey , Nicola Marchetti

We study the problem of communication over an additive white Gaussian noise (AWGN) channel with an AWGN feedback channel. When the feedback channel is noiseless, the classic Schalkwijk-Kailath (S-K) scheme is known to achieve capacity in a…

Information Theory · Computer Science 2017-01-04 Assaf Ben-Yishai , Ofer Shayevitz

Shannon channel capacity of an additive white Gaussian noise channel is the highest reliable transmission bit rate (RTBR) with arbitrary small error probability. However, the authors find that the concept is correct only when the channel…

Information Theory · Computer Science 2019-06-12 Bingli Jiao

Shannon's analysis of the fundamental capacity limits for memoryless communication channels has been refined over time. In this paper, the maximum volume $M_\avg^*(n,\epsilon)$ of length-$n$ codes subject to an average decoding error…

Information Theory · Computer Science 2016-12-28 Pierre Moulin

Many communication applications incorporate event-triggered behavior, where the conventional Shannon capacity may not effectively gauge performance. Consequently, we advocate for the concept of identification capacity as a more suitable…

Information Theory · Computer Science 2025-02-04 Ilya Vorobyev , Christian Deppe , Holger Boche

In this paper we fill the gap in previous works by proving the formula for entanglement-assisted capacity of quantum channel with additive constraint (such as bosonic Gaussian channel). The main tools are the coding theorem for…

Quantum Physics · Physics 2009-11-07 A. S. Holevo

A classical result in Information Theory states that the Gaussian noise is the worst-case additive noise in point-to-point channels, meaning that, for a fixed noise variance, the Gaussian noise minimizes the capacity of an additive noise…

Information Theory · Computer Science 2013-01-30 Ilan Shomorony , A. Salman Avestimehr

We use white Gaussian noise as a test signal for single-mode and multimode transmission links and estimate the link capacity based on a calculation of mutual information. We also extract the complex amplitude channel estimations and…

Non-asymptotic quantum Shannon theory analyses how to transmit quantum information across a quantum channel as efficiently as possible within a specified error tolerance, given access to a finite, fixed, number of channel uses. In a recent…

Quantum Physics · Physics 2025-03-18 Francesco Anna Mele , Giovanni Barbarino , Vittorio Giovannetti , Marco Fanizza

The capacity of a classical-quantum channel (or in other words the classical capacity of a quantum channel) is considered in the most general setting, where no structural assumptions such as the stationary memoryless property are made on a…

Quantum Physics · Physics 2016-11-17 Masahito Hayashi , Hiroshi Nagaoka

This paper provides new insight into the classical problem of determining both the capacity of the discrete-time channel with uniform output quantization and the capacity achieving input distribution. It builds on earlier work by Gallager…

Information Theory · Computer Science 2009-01-19 Yiyue Wu , Linda M. Davis , Robert Calderbank

In our companion paper [1], an information identity decomposition has been derived, which can be interpreted as a law of conservation of information flows in feedback systems. In this paper, we further investigate this decomposition result…

Systems and Control · Computer Science 2014-05-02 Bertrand Wechsler , Dan Eilat , Nicolas Limal

Consider a Gaussian relay network where a number of sources communicate to a destination with the help of several layers of relays. Recent work has shown that a compress-and-forward based strategy at the relays can achieve the capacity of…

Information Theory · Computer Science 2013-04-30 Ritesh Kolte , Ayfer Özgür

We study the input-entropy-constrained Gaussian channel capacity problem in the asymptotic high signal-to-noise ratio (SNR) regime. We show that the capacity-achieving distribution as SNR goes to infinity is given by a discrete Gaussian…

Information Theory · Computer Science 2026-01-16 Adway Girish , Shlomo Shamai , Emre Telatar

New upper bounds on the sum capacity of the two-user Gaussian interference channel are derived. Using these bounds, it is shown that treating interference as noise achieves the sum capacity if the interference levels are below certain…

Information Theory · Computer Science 2008-01-04 V. Sreekanth Annapureddy , Venugopal V. Veeravalli

The feedback capacity of the stationary Gaussian additive noise channel has been open, except for the case where the noise is white. Here we find the feedback capacity of the stationary first-order moving average additive Gaussian noise…

Information Theory · Computer Science 2007-07-16 Young-Han Kim

The capacity of the discrete-time channel affected by both additive Gaussian noise and Wiener phase noise is studied. Novel inner and outer bounds are presented, which differ of at most $6.65$ bits per channel use for all channel…

Information Theory · Computer Science 2017-01-19 Luca Barletta , Stefano Rini