Secure Computation Offloading Analysis for WPT-enabled UAV-assisted MEC Incorporating NOMA with Friendly Jammer in IoT Networks

This article investigates the efficacy of the secure computation offloading within an Internet of Things (IoT) network that employs wireless power transfer (WPT) -enabled unmanned aerial vehicle (UAV)-assisted mobile-edge computing (MEC) incorporating non-orthogonal multiple access (NOMA) over Nakagami-m fading channels. The proposed system is designed with the capability of offering proximate computational resources and substantial wireless power to clusters of resource-constrained edge devices (EDs). To proactively ensure secure communications, a friendly jammer (FJ) is strategically deployed to mitigate the adverse security threats posed by a multi-antenna passive eavesdropper. Accordingly, the assessment of the system’s secure computation offloading performance is facilitated through the derivation of a closed-form formulation termed secrecy successful computation probability (SSCP). This formulation explicitly considers the implications of imperfect channel state information (iCSI) and imperfect successive interference cancellation (iSIC), thereby ensuring realistic model applications. By aiming at maximizing SSCP and prioritizing an optimization algorithm that offers simplicity in implementation, computational efficiency, and minimal parameter-tuning requirements, an approach grounded on Ananya algorithm is formulated. Eventually, extensive numerical simulations have robustly validated the accuracy and viability of the system model, considering a wide range of critical parameters. Comparative findings demonstrate Ananya algorithm’s superiority on substantial aspects of rapid convergence towards optimal solutions and total computational duration compared to genetic algorithm (GA) and particle swarm intelligent (PSO).