Energy‐Efficient Joint Resource Management and Trajectory Planning in UAV‐Assisted NOMA‐Based Mobile Edge Computing Networks

With the increasing demand for high‐quality, computing‐intensive mobile services, the next‐generation networks must provide users with instantly available and sufficient computational resources. As a promising solution to this challenge, Unmanned Aerial Vehicle‐assisted Mobile Edge Computing (UAV‐assisted MEC) has gained significant attention in recent years. However, due to the limited energy available to the user equipment and UAVs, minimising the energy consumption remains a significant challenge. This article tackles the problem of energy‐efficient joint resource management and UAV trajectory optimisation in such networks by incorporating the Non‐Orthogonal Multiple Access (NOMA). To solve this non‐convex optimisation problem, it is divided into two sub‐problems, and the optimal solution to the main problem is then obtained by iteratively solving these two sub‐problems. According to the simulation results, incorporating Non‐Orthogonal Multiple Access (NOMA) method achieves a significant reduction of 44.44% in the overall utility function of the optimisation problem.