Is Gaussian Signalling Optimal for Covert Communications?

Date

2019

Authors

Yan, Shihao
Cong, Yirui
Hanly, Stephen V.
Zhou, Xiangyun

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Publisher

IEEE

Abstract

While Gaussian signalling is assumed in many studies on covert communications, its optimality has not been carefully investigated. In this work, we examine this optimality by considering the approach of upper bounding D(p 0 (y)∥p 1 (y)) as the covert communication constraint, where D(p 0 (y)∥p 1 (y)) is the Kullback-Leibler divergence from p 0 (y) to p 1 (y), p 0 (y) and p 1 (y) are the likelihood functions of the observation y at the warden under the null hypothesis (no covert transmission) and alternative hypothesis (a covert transmission occurs), respectively. Considering additive white Gaussian noise at both the receiver and the warden, we prove that Gaussian signalling is not optimal in terms of maximizing the mutual information of transmitted and received signals for covert communications with D(p 0 (y)∥p 1 (y)) ≤ 2ϵ 2 as the constraint. We also explicitly show a skew-normal signalling can outperform Gaussian signalling in terms of achieving higher mutual information subject to the same covertness constraint D(p 0 (y)∥p 1 (y)) ≤ 2ϵ 2 .

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Citation

Source

IEEE International Conference on Communications

Type

Conference paper

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DOI

10.1109/ICC.2019.8761750

Restricted until

2099-12-31