Computational energy efficient trajectory planning for UAV-enabled 6G MEC communication network

Abstract

In this work, we consider the unmanned aerial vehicle (UAV) as a flying MEC server to provide computational and communication resources to low-power sensor nodes. These sensor nodes are deployed uniformly over the predefined area. Due to conjunction or natural disaster, the central cloud system is not available. As a result, the quality of service is highly compromised. To ensure communication, UAV-MEC emerges as an effective solution to provide on-demand services. Therefore, by considering the limited serving capacity of UAVs, in this work, we formulate a joint computational energy efficiency problem by jointly optimizing the trajectory, computation, and communication resources. Furthermore, to address the computational complexity, we decouple the original optimization problem into a series of sub-problems and iteratively solve them. Moreover, extensive simulations were carried out to validate the proposed solution, and average results were produced. The numerical results demonstrate the proposed scheme’s effectiveness compared to other benchmark schemes.