Zhou, Gui, Pan, Cunhua, Ren, Hong, Wang, Kezhi, Chai, Kok Keong and Wong, Kai-Kit (2022) User cooperation for IRS-aided secure MIMO systems. Intelligent and Converged Networks, 3 (1). pp. 86-102. ISSN 2708-6240
|
Text
User_cooperation_for_IRS-aided_secure_MIMO_systems.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (3MB) | Preview |
Abstract
An intelligent reflecting surface (IRS) is proposed to enhance the physical layer security in the Rician fading channel wherein the angular direction of the eavesdropper (ED) is aligned with a legitimate user. A two-phase communication system under active attacks and passive eavesdropping is considered in this scenario. The base station avoids direct transmission to the attacked user in the first phase, whereas other users cooperate in forwarding signals to the attacked user in the second phase, with the help of IRS and energy harvesting technology. Under the occurrence of active attacks, an outage-constrained beamforming design problem is investigated under the statistical cascaded channel error model, which is solved by using the Bernstein-type inequality. An average secrecy rate maximization problem for the passive eavesdropping is formulated, which is then addressed by a low-complexity algorithm. The numerical results of this study reveal that the negative effect of the ED's channel error is larger than that of the legitimate user.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | energy harvesting, physical layer security, robust design, reconfigurable intelligent surface (RIS), intelligent reflecting surface (IRS) |
Subjects: | G900 Others in Mathematical and Computing Sciences H600 Electronic and Electrical Engineering H800 Chemical, Process and Energy Engineering |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | Rachel Branson |
Date Deposited: | 12 May 2022 10:48 |
Last Modified: | 12 May 2022 11:00 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/49100 |
Downloads
Downloads per month over past year