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相关论文: Binomial Channel: On the Capacity-Achieving Distri…

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We study the binomial channel and the structure of its capacity-achieving input and output distributions. It is known that the capacity-achieving input distribution is discrete and supported on finitely many points. The best previously…

信息论 · 计算机科学 2026-05-13 Mohammadamin Baniasadi , 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…

信息论 · 计算机科学 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,…

信息论 · 计算机科学 2019-11-18 Alex Dytso , Semih Yagli , H. Vincent Poor , Shlomo Shamai

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,…

信息论 · 计算机科学 2015-12-18 Jihad Fahs , Ibrahim Abou-Faycal

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…

信息论 · 计算机科学 2009-01-19 Yiyue Wu , Linda M. Davis , Robert Calderbank

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…

信息论 · 计算机科学 2018-07-23 Mahdi Cheraghchi , João Ribeiro

In this paper, the capacity of the additive white Gaussian noise (AWGN) channel, affected by time-varying Wiener phase noise is investigated. Tight upper and lower bounds on the capacity of this channel are developed. The upper bound is…

信息论 · 计算机科学 2015-09-22 M. Reza Khanzadi , Rajet Krishnan , Johan Söder , Thomas Eriksson

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.…

信息论 · 计算机科学 2021-05-06 Antonino Favano , Marco Ferrari , Maurizio Magarini , Luca Barletta

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

信息论 · 计算机科学 2025-01-28 Jonas Stapmanns , Catarina Dias , Luke Eilers , Jean-Pascal Pfister

Any physical channel of communication offers two potential reasons why its capacity (the number of bits it can transmit in a unit of time) might be unbounded: (1) Infinitely many choices of signal strength at any given instant of time, and…

信息论 · 计算机科学 2011-05-18 Sanjeev Khanna , Madhu Sudan

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…

信息论 · 计算机科学 2016-11-18 K. Alishahi , F. Marvasti , V. Aref , P. Pad

We present novel bounds on the capacity of the independent and identically distributed binary deletion channel. Four upper bounds are obtained by providing the transmitter and the receiver with genie-aided information on suitably-defined…

信息论 · 计算机科学 2008-10-07 Dario Fertonani , Tolga M. Duman

We analyze the quantum capacity of a unital quantum channel, using ideas from the proof of near-optimality of Petz recovery map [Barnum and Knill 2000] and give an upper bound on the quantum capacity in terms of regularized output $2$-norm…

量子物理 · 物理学 2018-03-07 Anurag Anshu

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…

信息论 · 计算机科学 2017-11-17 Jihad Fahs , Ibrahim Abou-Faycal

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…

信息论 · 计算机科学 2024-01-11 Luca Barletta , Alex Dytso , Shlomo Shamai

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…

信息论 · 计算机科学 2025-08-12 Reza K. Farsani , Wei Yu

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…

信息论 · 计算机科学 2026-03-26 Haiyang Wang , Luca Barletta , Alex Dytso

We study the capacity regions of broadcast channels with binary inputs and symmetric outputs. We study the partial order induced by the more capable ordering of broadcast channels for channels belonging to this class. This study leads to…

信息论 · 计算机科学 2010-01-14 Yanlin Geng , Chandra Nair , Shlomo Shamai , Zizhou Vincent Wang

We consider multiple access communication on a binary input additive white Gaussian noise channel using randomly spread code division. For a general class of symmetric distributions for spreading coefficients, in the limit of a large number…

信息论 · 计算机科学 2008-03-11 Satish Babu Korada , Nicolas Macris

Binary-input memoryless channels with a runlength constrained input are considered. Upper bounds to the capacity of such noisy runlength constrained channels are derived using the dual capacity method with Markov test distributions…

信息论 · 计算机科学 2016-11-17 Andrew Thangaraj
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