On the Discreteness of Capacity-Achieving Distributions for the Censored Channel

Authors

A. Behboodi, G. Alirezaei, R. Mathar,

Abstract

        The censored channel is one of the fundamental channels in information theory, which belongs to the class of non-linear channels. It is modeled by cascading an additive noise channel with a clipping operator. This paper is concerned with the information theoretic capacity of this channel. A necessary and sufficient condition for optimality of the input distribution is derived and it is shown that the capacity-achieving input distribution for the amplitude-limited censored channel has only a finite number of mass points. This result holds for a large class of noise distributions including additive Gaussian noise.

BibTEX Reference Entry 

@inproceedings{BeAlMa17b,
	author = {Arash Behboodi and Gholamreza Alirezaei and Rudolf Mathar},
	title = "On the Discreteness of Capacity-Achieving Distributions for the Censored Channel",
	booktitle = "2017 {IEEE} International Symposium on Information Theory (ISIT'17)",
	address = {Aachen, Germany},
	month = Jun,
	year = 2017,
	}

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