Dynamic UAV Relay-Assisted MEC-NOMA for Optimal Power Distribution in Multiuser Vehicular Networks

To enhance the performance of vehicular networking systems and reduce power consumption, this paper utilizes Mobile Edge Computing (MEC) to achieve optimal power allocation in a multiuser cluster for the downlink of Non-Orthogonal Multiple Access (NOMA) systems. We propose a MEC-NOMA system supported by a dynamic UAV relay cooperative vehicular network. This research first investigates the globally optimal power allocation policy for downlink users within the MEC-NOMA system by examining the spatial dynamics of UAV relay planning for collaborative vehicular networking deployments, and further validates our findings through Monte Carlo simulations. The simulation results demonstrate a significant improvement in the system's performance for multiuser clustering under the dynamic UAV relay cooperative vehicular networking setup, specifically in terms of energy consumption and total user rate, when compared to traditional Frequency Division Multiple Access (FDMA) schemes.