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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

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

The capacity-achieving input distribution of the discrete-time, additive white Gaussian noise (AWGN) channel with an amplitude constraint is discrete and seems difficult to characterize explicitly. A dual capacity expression is used to…

Information Theory · Computer Science 2015-11-30 Andrew Thangaraj , Gerhard Kramer , Georg Bocherer

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

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…

Information Theory · Computer Science 2015-09-22 M. Reza Khanzadi , Rajet Krishnan , Johan Söder , Thomas Eriksson

The capacity of a complex and discrete-time memoryless additive white Gaussian noise (AWGN) channel under three constraints, namely, input average power, input amplitude and output delivered power is studied. The output delivered power…

Information Theory · Computer Science 2020-04-27 Morteza Varasteh , Borzoo Rassouli , Bruno Clerckx

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

In this paper, we consider single- and multi-user Gaussian channels with feedback under expected power constraints and with non-vanishing error probabilities. In the first of two contributions, we study asymptotic expansions for the…

Information Theory · Computer Science 2016-09-22 Lan V. Truong , Silas L. Fong , Vincent Y. F. Tan

In this paper, we derive upper and lower bounds as well as a simple closed-form approximation for the capacity of the continuous-time, bandlimited, additive white Gaussian noise channel in a three-dimensional free-space electromagnetic…

Information Theory · Computer Science 2017-02-27 Richard J. Barton

This paper investigates the asymptotic expansion for the size of block codes defined for the additive white Gaussian noise (AWGN) channel with feedback under the following setting: A peak power constraint is imposed on every transmitted…

Information Theory · Computer Science 2014-10-14 Silas L. Fong , Vincent Y. F. Tan

We investigate the Peak-Power Limited (PPL) Additive White Gaussian Noise (AWGN) channels in which the signal is band-limited, and its instantaneous power cannot exceed the power P. This model is relevant to many communication systems;…

Information Theory · Computer Science 2024-12-10 Michael Peleg , Shlomo Shamai

Information transmission over discrete-time channels with memoryless additive noise obeying a Cauchy, rather than Gaussian, distribution, are studied. The channel input satisfies an average power constraint. Upper and lower bounds to such…

Information Theory · Computer Science 2024-11-19 Shuqin Pang , Wenyi Zhang

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

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

This paper provides an upper-bound for the capacity of the underwater acoustic (UWA) channel with dominant noise sources and generalized fading environments. Previous works have shown that UWA channel noise statistics are not necessary…

Information Theory · Computer Science 2014-04-29 Mustafa A. Kishk , Ahmed M. Alaa

In some applications, the variance of additive measurement noise depends on the signal that we aim to measure. For instance, additive Gaussian signal-dependent noise (AGSDN) channel models are used in molecular and optical communication.…

Information Theory · Computer Science 2017-06-05 Hamid Ghourchian , Gholamali Aminian , Amin Gohari , Mahtab Mirmohseni , Masoumeh Nasiri-Kenari

For a continuous-time additive white Gaussian noise (AWGN) channel with possible feedback, it has been shown that as sampling gets infinitesimally fine, the mutual information of the associative discrete-time channels converges to that of…

Information Theory · Computer Science 2020-08-26 Guangyue Han , Shlomo Shamai

We consider a continuous-time bandlimited additive white Gaussian noise channel with 1-bit output quantization. On such a channel the information is carried by the temporal distances of the zero-crossings of the transmit signal. The set of…

Information Theory · Computer Science 2017-09-25 Sandra Bender , Meik Dörpinghaus , Gerhard Fettweis

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

Tight bounds on the minimum mean square error for the additive Gaussian noise channel are derived, when the input distribution is constrained to be epsilon-close to a Gaussian reference distribution in terms of the Kullback--Leibler…

Statistics Theory · Mathematics 2018-04-27 Michael Fauss , Alex Dytso , Abdelhak M. Zoubir , H. Vincent Poor
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