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Under which condition is quantization optimal? We address this question in the context of the additive uniform noise channel under peak amplitude and cost constraints. We compute analytically the capacity-achieving input distribution as a…

Information Theory · Computer Science 2025-10-15 Jonas Stapmanns , Catarina Dias , Luke Eilers , Tobias Kühn , Jean-Pascal Pfister

We study the classical problem of characterizing the channel capacity and its achieving distribution in a generic fashion. We derive a simple relation between three parameters: the input-output function, the input cost function and the…

Information Theory · Computer Science 2017-11-17 Jihad Fahs , Ibrahim Abou-Faycal

This work considers a Poisson noise channel with an amplitude constraint. It is well-known that the capacity-achieving input distribution for this channel is discrete with finitely many points. We sharpen this result by introducing upper…

Information Theory · Computer Science 2021-07-30 Alex Dytso , Luca Barletta , Shlomo Shamai

This paper studies an $n$-dimensional additive Gaussian noise channel with a peak-power-constrained input. It is well known that, in this case, when $n=1$ the capacity-achieving input distribution is discrete with finitely many mass points,…

Information Theory · Computer Science 2019-11-18 Alex Dytso , Semih Yagli , H. Vincent Poor , Shlomo Shamai

The capacity of multiple-input multiple-output additive white Gaussian noise channels is investigated under peak amplitude constraints on the norm of the input vector. New insights on the capacity-achieving input distribution are presented.…

Information Theory · Computer Science 2021-05-06 Antonino Favano , Marco Ferrari , Maurizio Magarini , Luca Barletta

We study the maximum achievable differential entropy at the output of a system assigning to each input X the sum X+N, with N a given noise with probability law absolutely continuous with respect to the Lebesgue measure and where the input…

Optimization and Control · Mathematics 2016-02-04 Francisco J. Piera

We show that the uniform distribution minimizes entropy among all one-dimensional symmetric log-concave distributions with fixed variance, as well as various generalizations of this fact to R\'enyi entropies of orders less than 1 and with…

Information Theory · Computer Science 2021-10-20 Mokshay Madiman , Piotr Nayar , Tomasz Tkocz

This paper considers the problem of secret-key agreement with public discussion subject to a peak power constraint $A$ on the channel input. The optimal input distribution is proved to be discrete with finite support. The result is obtained…

Information Theory · Computer Science 2018-05-09 Marwen Zorgui , Zouheir Rezki , Basel Alomair , Mohamed-Slim Alouini

This work considers a binomial noise channel. The paper can be roughly divided into two parts. The first part is concerned with the properties of the capacity-achieving distribution. In particular, for the binomial channel, it is not known…

Information Theory · Computer Science 2024-01-24 Ian Zieder , Antonino Favano , Luca Barletta , Alex Dytso

This paper studies secrecy-capacity of an $n$-dimensional Gaussian wiretap channel under a peak-power constraint. This work determines the largest peak-power constraint $\bar{\mathsf{R}}_n$ such that an input distribution uniformly…

Information Theory · Computer Science 2023-05-17 Antonino Favano , Luca Barletta , Alex Dytso

The sum-rate capacity of the parallel Gaussian interference channel is shown to be achieved by independent transmission across sub-channels and treating interference as noise in each sub-channel if the channel coefficients and power…

Information Theory · Computer Science 2009-03-04 Xiaohu Shang , Biao Chen , Gerhard Kramer , H. Vincent Poor

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

We study the amplitude-constrained additive white Gaussian noise channel. It is well known that the capacity-achieving input distribution for this channel is discrete and supported on finitely many points. The best known bounds show that…

Information Theory · Computer Science 2026-03-26 Haiyang Wang , Luca Barletta , Alex Dytso

This work considers a discrete-time Poisson noise channel with an input amplitude constraint $\mathsf{A}$ and a dark current parameter $\lambda$. It is known that the capacity-achieving distribution for this channel is discrete with…

Information Theory · Computer Science 2024-01-11 Luca Barletta , Alex Dytso , Shlomo Shamai

We investigate the limits of communication over the discrete-time Additive White Gaussian Noise (AWGN) channel, when the channel output is quantized using a small number of bits. We first provide a proof of our recent conjecture on the…

Information Theory · Computer Science 2008-05-15 Jaspreet Singh , Onkar Dabeer , Upamanyu Madhow

Evaluating the channel capacity is one of many key problems in information theory. In this work we derive rather-mild sufficient conditions under which the capacity is finite and achievable. These conditions are derived for generic,…

Information Theory · Computer Science 2015-12-18 Jihad Fahs , Ibrahim Abou-Faycal

The optimal rate at which information can be sent through a quantum channel when the transmitted signal must simultaneously carry some minimum amount of energy is characterized. To do so, we introduce the quantum-classical analogue of the…

Quantum Physics · Physics 2025-01-10 Bishal Kumar Das , Lav R. Varshney , Vaibhav Madhok

The quantum capacity of thermal noise channel is studied. The extremal input state is obtained at the postulation that the coherent information is convex or concave at its vicinity. When the input energy tends to infinitive, it is verified…

Quantum Physics · Physics 2007-05-23 Xiao-yu Chen

The per-sample zero-dispersion channel model of the optical fiber is considered. It is shown that capacity is uniquely achieved by an input probability distribution that has continuous uniform phase and discrete amplitude that takes on…

Information Theory · Computer Science 2018-09-25 Jihad Fahs , Aslan Tchamkerten , Mansoor I. Yousefi

A practical communication channel often suffers from constraints on input other than the average power, such as the peak power constraint. In order to compare achievable rates with different constellations as well as the channel capacity…

Information Theory · Computer Science 2011-05-17 Shiro Ikeda , Kazunori Hayashi , Toshiyuki Tanaka
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