面向用户的无人机辅助MEC网络性能优化
2024,46(6):166-173
薛建彬
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050，xuejb@lut.edu.cn,hjzmaster@163.com
武清清
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050
张海军
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050，xuejb@lut.edu.cn,hjzmaster@163.com
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050，xuejb@lut.edu.cn,hjzmaster@163.com
武清清
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050
张海军
兰州理工大学 计算机与通信学院, 甘肃 兰州 730050，xuejb@lut.edu.cn,hjzmaster@163.com
摘要：
针对具有高视距和高机动性特性的无人机(unmanned aerial vehicle,UAV)辅助移动边缘计算(mobile edge computing,MEC)进行空-地高效数据通信系统中无人机能耗对通信质量造成直接影响和多用户多业务需求的问题,提出了一种在确保用户体验性的前提下最小化系统能耗的交替迭代优化算法,通过建立包含无人机轨迹、信道模型、本地计算模型、计算卸载模型和无人机能耗五个子模型的UAV-MEC网络系统,联合优化无人机轨迹、用户卸载量和无人机功率,对系统能耗进行了优化。通过仿真结果表明了在与已有基准方案相比较时,终端用户的计算能耗减少了35%,系统性的整体性能得到了显著改善。
针对具有高视距和高机动性特性的无人机(unmanned aerial vehicle,UAV)辅助移动边缘计算(mobile edge computing,MEC)进行空-地高效数据通信系统中无人机能耗对通信质量造成直接影响和多用户多业务需求的问题,提出了一种在确保用户体验性的前提下最小化系统能耗的交替迭代优化算法,通过建立包含无人机轨迹、信道模型、本地计算模型、计算卸载模型和无人机能耗五个子模型的UAV-MEC网络系统,联合优化无人机轨迹、用户卸载量和无人机功率,对系统能耗进行了优化。通过仿真结果表明了在与已有基准方案相比较时,终端用户的计算能耗减少了35%,系统性的整体性能得到了显著改善。
基金项目：
甘肃省自然科学基金资助项目(20JR10RA182)
甘肃省自然科学基金资助项目(20JR10RA182)
User-oriented UAV-aided MEC network performance optimization
XUE Jianbin
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China,xuejb@lut.edu.cn,hjzmaster@163.com
WU Qingqing
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China
ZHANG Haijun
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China,xuejb@lut.edu.cn,hjzmaster@163.com
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China,xuejb@lut.edu.cn,hjzmaster@163.com
WU Qingqing
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China
ZHANG Haijun
School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China,xuejb@lut.edu.cn,hjzmaster@163.com
Abstract：
Aiming at the problem that the energy consumption of UAV(unmanned aerial vehicle) with high visual range and high maneuverability characteristics in the air ground efficient data communication system assisted by MEC(mobile edge computing) of UAV with high visual range and high mobility characteristics has a direct impact on the communication quality and multi-user and multi service requirements, a alternating iterative optimization method was proposed to minimize the system energy consumption on the premise of ensuring user experience. By establishing a UAV-MEC network system containing five sub models of UAV trajectory, channel model, local computing model, computing unloading model and UAV energy consumption, the UAV trajectory, user unloading volume and UAV power were jointly optimized. The system energy consumption was optimized. The simulation results show that compared with existing benchmark schemes, the computational energy consumption of end users reduce by 35%, and the overall performance of the system is improved.
Aiming at the problem that the energy consumption of UAV(unmanned aerial vehicle) with high visual range and high maneuverability characteristics in the air ground efficient data communication system assisted by MEC(mobile edge computing) of UAV with high visual range and high mobility characteristics has a direct impact on the communication quality and multi-user and multi service requirements, a alternating iterative optimization method was proposed to minimize the system energy consumption on the premise of ensuring user experience. By establishing a UAV-MEC network system containing five sub models of UAV trajectory, channel model, local computing model, computing unloading model and UAV energy consumption, the UAV trajectory, user unloading volume and UAV power were jointly optimized. The system energy consumption was optimized. The simulation results show that compared with existing benchmark schemes, the computational energy consumption of end users reduce by 35%, and the overall performance of the system is improved.
收稿日期：
2022-05-31
2022-05-31
