无人机辅助MEC系统中的联合计算卸载和轨迹设计  

Joint Computing Offloading and Trajectory Design in UAV-enabled MEC System

作　　者：许晨旭[1] 曹润宇 薛志钢[1] 张善新 XU Chenxu;CAO Runyu;XUE Zhigang;ZHANG Shanxin(Special Equipment Safety Supervision Inspection Institute of Jiangsu Province,Wuxi 214025,China;School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China)

机构地区：[1]江苏省特种设备安全监督检验研究院,无锡214025 [2]江南大学物联网工程学院,无锡214122

出　　处：《武汉理工大学学报（交通科学与工程版）》2024年第1期7-12,共6页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家市场监督管理总局科技计划项目(2021MK043、2021MK044)。

摘　　要：文中提出了一种无人机辅助移动边缘计算(MEC)系统,其中一架配备计算资源的无人机作为飞行基站(BS)处理从用户迁移来的应用任务,以节省用户设备的能耗.考虑了一种通用的瑞森衰落信道模型,通过联合优化无人机轨迹、用户发射功率、用户调度和比特分配,以最小化所有用户设备的平均能耗.设计了一种基于迭代分块连续上界最小化算法,并引入二次惩罚项进行交替求解.结果表明:文中所提出的联合优化方案优于其他基准方案,能显著降低用户的能量消耗.A UAV-aided moving edge calculation(MEC)system was proposed.One UAV equipped with computing resources was used as a flight base station(BS)to handle the application tasks migrated from users,so as to save energy consumption of user equipment.A general Ruisen fading channel model was considered.By jointly optimizing UAV trajectory,user transmit power,user scheduling and bit allocation,the average energy consumption of all user equipments was minimized.A continuous upper bound minimization algorithm based on iterative block was designed,and a quadratic penalty term was introduced to solve it alternately.The results show that the joint optimization scheme proposed in this paper is superior to other benchmark schemes and can significantly reduce the energy consumption of users.

关 键 词：移动边缘计算 无人机 能量消耗 计算卸载 轨迹优化 

分 类 号：U674.771[交通运输工程—船舶及航道工程]