Secrecy Energy Efficiency Optimization for Reconfigurable Intelligent Surface-Aided Multiuser MISO Systems

Abstract

Currently, the reconfigurable intelligent surface (RIS) has been applied to improve the physical layer security in wireless networks. In this paper, we focus on the secure transmission in RIS-aided multiple-input single-output (MISO) systems. Specifically, by assuming that only imperfect channel state information (CSI) of the eavesdropper can be obtained, we investigated the robust secrecy energy efficiency (SEE) optimization via jointly designing the active beamforming (BF), artificial noise (AN) at Alice, and the passive phase shifter at the RIS. The formulated problem is hard to handle due to the complicated secrecy rate expression as well as the infinite constraints introduced by the CSI uncertainties. By utilizing the Taylor expansion, we transformed the fractional programming into a convex problem, while all the constraints are approximated via the successive convex approximation and constrained concave-convex procedure. Then, by using the extended S-Lemma, we transform the infinite constraints into linear matrix inequality, which is convex. Finally, an alternate optimization (AO) algorithm was proposed to solve the reformulated problem. Simulation results demonstrated the performance of the proposed design.

Optimization of Secure Computation Efficiency in UAV-Enabled RIS-Assisted MEC-IoT Networks With Aerial and Ground Eavesdroppers

“…Specifically, the secure computation efficiency (SCE) was optimized, under computing, transmit power, time slot, and RIS's phase shifts constraints. Assuming imperfect channel state information (CSI) in the GE's link, a downlink multiple-input single-output (MISO) RIS-assisted network was also presented in [9]. The optimization efforts involved the adjustment of artificial noise, active beamforming, and RIS's passive phase shifter to enhance secrecy energy efficiency.…”