Secrecy Offloading Analysis of NOMA-based UAV-aided MEC in IoT Networks with Imperfect CSI and SIC

Nonorthogonal multiple access (NOMA) increases spectrum efficacy by permitting multiple devices to share link resources. It can be used to provide convenient offloading computing services for edge devices (EDs) in unmanned aerial vehicle (UAV) and mobile-edge computing (MEC) networks. However, due to the Line-of-Sight (LoS) of UAV transmission, NOMA-based UAV-MEC systems are susceptible to information eavesdropping. In this paper, we investigate a secure offloading model for a NOMA-based UAV-aided MEC in Internet of Things (IoT) network concerning an aerial eavesdropper (EAV) that considers imperfect channel state information (ipCSI) and imperfect successive interference cancellation (ipSIC).We derive the expression of secrecy successful computation probability (SSCP) across the entire system to analyze EAV’s impact on the performance of the NOMA-based UAV-aided MEC in IoT networks. In addition, we present a formulation of an optimization problem that optimizes the SSCP through the optimization of the UAV’s altitude and location, as well as the offloading ratio. To address this issue, a genetic algorithm (GA)-based approach was implemented. The results of our study were corroborated by the Monte Carlo simulations, which assessed system performance by considering multiple system parameters including the UAV’s location, altitude, average transmit signal-to-noise ratio (SNR), and offloading ratio.