NOMA-Enabled Mobile Edge Computing for Air-to-Ground Integrated IoV Networks

With the rapid development of Internet of Vehicles (IoV) networks, vehicular communication scenarios characterized by high density and high dynamics present significant challenges in terms of low latency and high reliability for task processing. Motivated by the above, this paper investigates the task offloading delay optimization problem in air-to-ground integrated IoV networks. First, we utilize the non-orthogonal multiple access (NOMA) technology to enable efficient communication between the autonomous aerial vehicle (AAV) and intelligent connected vehicles (ICVs). Next, we formulate the problem of minimizing total delay. Then, we solve the formulated total delay minimization problem using iterative optimization. In this process, the task offloading ratio, channel allocation, transmission power, and AAV trajectory are optimized. Finally, the simulation results validate the robustness of the proposed scheme under variations in vehicle density, task load, AAV speed, and bandwidth. Compared to the state-of-the-art schemes, the proposed scheme reduces total delay by 32.7%.