Aerial RIS Aided NOMA Networks with Optimized Secrecy Metrics Performance

Abstract

Reconfigurable Intelligent Surface (RIS) technology is a promising technique for enhancing the performance of reconfigurable next-generation wireless networks. In this paper, we investigate the physical layer security of the downlink in RIS-aided non-orthogonal multiple access (NOMA) networks in the presence of an eavesdropper. To characterize the network performance, the expected value of the new channel statistics is derived for the reflected links in the case of Rayleigh fading distribution. Furthermore, the performance of the proposed network is evaluated in terms of the secrecy outage probability (SOP) and the strictly positive secrecy capacity (SPSC). To optimize these metrics, we employ the multi-objective artificial vultures optimization algorithm (MOAVOA), using the power allocation coefficients of the nearby and distant users as key parameters. Two case studies are considered in simulation: perfect channel state information (CSI) and imperfect CSI.