基于无人机辅助的NOMA-MEC系统能效最大化方法

Energy Efficiency Maximization Method of NOMA-MEC System Based on UAV Assistance

摘要

针对无人机(UAV)辅助的移动边缘计算(MEC)系统执行计算任务时能耗约束显著问题,构建无人机兼具计算单元与中继节点的系统模型,并用非正交多址(NOMA)技术提高频谱效率.在满足地面用户的任务需求下,通过对用户的通信调度、任务计算分配、发射功率和无人机的飞行轨迹优化,使整个系统的能量效率最大化.将无法直接求解的非凸混合整数非线性分式规划(MINLFP)问题分解成易于求解的子问题并迭代求解.目标函数的分式形式采用Dinkelbach方法求解,该方法利用连续凸近似(SCA)将分式问题的原始子问题转化为凸形式.仿真结果表明,该方法可提高系统能效.

Abstract

Aiming at the problem of significant energy consumption constraints when unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) systems performed computing tasks, we constructed a system model of UAV that combined computing units and relay nodes, and used non-orthogonal multiple access (NOMA) technology to improve spectral efficiency. By meeting the task requirements of ground users, the energy efficiency of the entire system was maximized by optimizing user communication scheduling, task computation offloading, transmit power, and UAV flight trajectory. We decomposed a non-convex mixed-integer nonlinear fractional programming (MINLFP) problem that could not be directly solved into easily solvable subproblems and iteratively solved them. The fractional form of the objective function was solved by using the Dinkelbach method, which utilized successive convex approximation (SCA) to transform the original subproblems of the fractional problem into convex form. The simulation results show that the proposed method can improve the energy efficiency of the system.

关键词

无人机 / 移动边缘计算 / 资源分配 / 轨迹优化

Key words

unmanned aerial vehicle / mobile edge computing / resource allocation / trajectory optimization

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基金资助

国家自然科学基金(62261056)