摘要
为了缓解移动边缘计算(Mobile Edge Computing,MEC)网络任务卸载中面临的频谱资源稀缺问题,研究了一种无人机辅助的认知MEC网络架构。将认知无线电技术与边缘计算相结合,在同一个频段内存在多个主用户的情况下,利用无人机搭载的边缘计算服务器为次用户提供计算服务,以进一步提高边缘计算网络的频谱利用率。以最小化次用户和无人机的加权总能耗为目标,在主用户干扰温度约束、次用户任务完成约束以及无人机的轨迹约束下对次用户的中央处理器(Central Processing Unit,CPU)频率、卸载功率以及无人机轨迹建立了联合优化问题。利用连续凸近似(Successive Convex Approximation,SCA)方法对所建立的非凸问题进行3阶段交替求解。仿真结果验证了所提算法的有效性。
In order to tackle the spectrum scarcity problem faced by task offloading,a cognitive unmanned aerial vehicle(UAV)enabled mobile edge computing(MEC)network is studied.Cognitive radio technology is combined with edge computing,and the UAV-enabled MEC server provides computing service to the secondary users(SUs),in the presence of multiple primary users(PUs)that operate in the same spectrum band,so as to further improve the spectrum utilization of edge computing network.An optimization problem of jointly optimizing the central processing unit(CPU)frequency,offloading power of the SUs and the UAV trajectory is formulated to minimize the weighted sum energy consumption of the UAV and the SUs under the constraints of the PUs'interference temperature,the SUs'task completion and the UAV trajectory.The formulated non-convex problem is solved by our proposed three-step alternating optimization algorithm based on successive convex approximation(SCA)method.Numerical results show the efficiency of our proposed scheme.
作者
刘伯阳
杨宁乐
马杰
万奕尧
李明
LIU Boyang;YANG Ningle;MA Jie;WAN Yiyao;LI Ming(School of Communications and Information Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China;National Key Lab of Blind Signal Processing,Chengdu 610041,China)
出处
《西安邮电大学学报》
2021年第1期20-27,共8页
Journal of Xi’an University of Posts and Telecommunications
基金
国家自然科学基金项目(61701399)
陕西省自然科学基础研究计划项目(2020JQ-851)
陕西省教育厅专项科研计划项目(19JK0796)
陕西省普通高校青年杰出人才支持计划项目。
关键词
移动边缘计算
无人机
认知无线电
加权总能耗
交替优化
mobile edge computing(MEC)
unmanned aerial vehicle(UAV)
cognitive radio
weighted sum energy
alternating optimization
