Secrecy Offloading Analysis for UAV-Assisted NOMA-MEC in IoT Networks with Imperfect CSI

This study investigated secrecy offloading in uplink nonorthogonal multiple access (NOMA)-based mobile-edge computing (MEC) in Internet of Things (IoT) systems employing unmanned aerial vehicle (UAV). Specifically, two resource-limited edge device (ED) try to offload their tasks to a UAV equipped a MEC processor in the presence of a passive eavesdropper. We calculate secrecy successful computation probability (SSCP) to evaluate system secrecy. We also present an optimization problem formulation that optimizes the SSCP by optimizing UAV location and altitude. Artificial bee colony (ABC) algorithm was used to solve this problem. The Monte Carlo simulation results supported the accuracy of our study based on system performance simulations using various system parameters such as the average transmit signal-to-noise ratio (SNR), location, and altitude of the UAV.