Reference : Intelligent Reflecting Surface Enhanced Secure Transmission Against Both Jamming and ...

	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/49253

Title :	Intelligent Reflecting Surface Enhanced Secure Transmission Against Both Jamming and Eavesdropping Attacks
Language :	English
Author, co-author :	Sun, Yifu []
	An, Kang []
	Luo, Junshan []
	Zhu, Yonggang []
	Zheng, Gan []
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Publication date :	13-Aug-2021
Journal title :	IEEE Transactions on Vehicular Technology
Publisher :	IEEE
Volume :	70
Issue/season :	10, Oct. 2021
Pages :	11017 - 11022
Peer reviewed :	Yes (verified by ORBilu)
ISSN :	0018-9545
e-ISSN :	1939-9359
Abstract :	[en] Both the jammer and the eavesdropper pose severe threat to wireless communications due to the broadcast nature of wireless channels. In this paper, an intelligent reflecting surface (IRS) assisted secure communication system is considered, where a base station (BS) wishes to reliably convey information to a user, in the presence of both a jammer and an eavesdropper whose channel state information (CSI) is not perfectly known. Specifically, we aim to maximize the system achievable rate by jointly designing the BS’s transmit beamforming and the IRS’s reflect beamforming with imperfect CSI, while limiting the information leakage to the potential eavesdropper. Due to the non-convexity and intractability of the original problem induced by the CSI uncertainty, we utilize the auxiliary variables and General Sign-Definiteness transformation to convert the original optimization problem into a tractable convex optimization problem, and then obtain the high-quality optimal solution by using the successive convex approximation and penalty convex concave procedure. Numerical simulations demonstrate the superiority of our proposed optimization algorithm compared with existing approaches, and also reveal the impact of key parameters on the achievable system performance.
Funders :	10.13039/501100001809-National Natural Science Foundation of China (Grant Number: U19B214 and 61901502) - Foundation strengthening Plan Area Fund (Grant Number: 2019-JCJQ-JJ-212 and 2019-JCJQ-JJ226)
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/49253
DOI :	10.1109/TVT.2021.3104580
Other URL :	https://ieeexplore.ieee.org/document/9513582
FnR project :	FnR ; FNR14773976 > Bjorn Ottersten > RISOTTI > Reconfigurable Intelligent Surfaces For Smart Cities > 01/06/2021 > > 2020

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