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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

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 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 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

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

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

We study the amplitude-constrained additive white Gaussian noise (AWGN) channel from the perspective of near-optimal input distributions. While it is known that the capacity-achieving input is discrete with finitely many mass points, the…

Information Theory · Computer Science 2026-04-17 Luca Barletta , Alex Dytso

We consider the problem of estimating an upper bound on the capacity of a memoryless channel with unknown channel law and continuous output alphabet. A novel data-driven algorithm is proposed that exploits the dual representation of…

Information Theory · Computer Science 2024-01-25 Christian Häger , Erik Agrell

This paper shows that the logarithm of the epsilon-error capacity (average error probability) for n uses of a discrete memoryless channel is upper bounded by the normal approximation plus a third-order term that does not exceed 1/2 log n +…

Information Theory · Computer Science 2013-10-25 Marco Tomamichel , Vincent Y. F. Tan

We consider the problem of estimating the support size of a distribution $D$. Our investigations are pursued through the lens of distribution testing and seek to understand the power of conditional sampling (denoted as COND), wherein one is…

Data Structures and Algorithms · Computer Science 2022-11-23 Diptarka Chakraborty , Gunjan Kumar , Kuldeep S. Meel

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

The channel law for amplitude-modulated solitons transmitted through a nonlinear optical fibre with ideal distributed amplification and a receiver based on the nonlinear Fourier transform is a noncentral chi-distribution with $2n$ degrees…

We study the growth of the support size of the capacity-achieving input distribution for the amplitude-constrained additive white Gaussian noise (AWGN) channel. While it is known since Smith (1971) that the optimal input is discrete with…

Information Theory · Computer Science 2025-12-04 Haiyang Wang

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

A channel coding achievability bound expressed in terms of the ratio between two Neyman-Pearson $\beta$ functions is proposed. This bound is the dual of a converse bound established earlier by Polyanskiy and Verd\'{u} (2014). The new bound…

Information Theory · Computer Science 2016-01-25 Wei Yang , Austin Collins , Giuseppe Durisi , Yury Polyanskiy , H. Vincent Poor

The two-user broadcast channel (BC) with receivers connected by bidirectional cooperation links of finite capacities, known as conferencing decoders, is considered. A novel capacity region outer bound is established based on multiple…

Information Theory · Computer Science 2025-08-12 Reza K. Farsani , Wei Yu

The cognitive interference channel is an interference channel in which one transmitter is non-causally provided with the message of the other transmitter. This channel model has been extensively studied in the past years and capacity…

Information Theory · Computer Science 2010-03-24 Stefano Rini , Daniela Tuninetti , Natasha Devroye

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

In this paper, we obtain a family of lower bounds for the sum capacity of Code Division Multiple Access (CDMA) channels assuming binary inputs and binary signature codes in the presence of additive noise with an arbitrary distribution. The…

Information Theory · Computer Science 2016-11-18 K. Alishahi , F. Marvasti , V. Aref , P. Pad

Communication channels are said to be underspread if their coherence time is greater than their delay spread. In such cases it can be shown that in the infinite bandwidth limit the information capacity tends to that of a channel with…

Information Theory · Computer Science 2014-06-24 Steven Herbert , Ian Wassell , Tian-Hong Loh
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