Resource Allocation Method for Unmanned Aerial Vehicle-Assisted and User Cooperation Non-Linear Energy Harvesting Mobile Edge Computing System

Abstract

Abstract:Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading, a resource allocation method for unmanned aerial vehicle (UAV)-assisted and user cooperation non-linear energy harvesting mobile edge computing (MEC) system is proposed. The UAV equipped with an MEC server is introduced to provide energy and computing services for the remote user group to alleviate the doubly near-far problem in a large range suffered by the remote user group. The doubly near-far problem in a small range existing in both nearby and remote user groups is mitigated by user cooperation. The specific user cooperation strategy is that the user near the base station or the UAV is used as a relay to transfer the computing task of the user far from the base station or the UAV to the MEC server for computing. By jointly optimizing users’ offloading time, users’ transmitting power, and the hovering position of the UAV, the resource allocation problem is modeled as a nonlinear programming problem with the objective of maximizing computation efficiency. The suboptimal solution is obtained by adopting the differential evolution algorithm. Simulation results show that, compared with the resource allocation method based on genetic algorithm and the without user cooperation method, the proposed method has higher computation efficiency.

Key words:mobile edge computing (MEC), non-linear energy harvesting, unmanned aerial vehicle (UAV), user cooperation, resource allocation

摘要：针对能量收集和计算卸载过程中，远距离用户群遭受大范围内的双重远近问题和远近用户群中存在的小范围内的双重远近问题，提出了一种无人机（UAV）协助和用户协作的非线性能量收集移动边缘计算（MEC）系统资源分配方法。引入搭载MEC服务器的无人机为远距离用户群提供能量和计算服务，以缓解其遭受的大范围双重远近问题。通过用户协作来缓解远近用户群中存在的小范围双重远近问题。具体的用户协作策略是：靠近基站或UAV的用户作为中继，将远离基站或UAV的用户的计算任务转移到MEC服务器进行计算。通过联合优化用户卸载时间、用户发射功率和无人机悬停位置，将资源分配问题建模成以最大化计算效率为目标的非线性规划问题。采用差分进化算法得到次优解。仿真结果表明，与基于遗传算法的资源分配方法和无用户协作的方法相比，提出的方法具有更高的计算效率。

关键词:移动边缘计算，非线性能量收集，无人机，用户协作，资源分配

CLC Number:

TN915.65

HE Ximei, ZHAO Yisheng, XU Zhihong, CHEN Yong. Resource Allocation Method for Unmanned Aerial Vehicle-Assisted and User Cooperation Non-Linear Energy Harvesting Mobile Edge Computing System[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(6): 1220-1231.

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