6G无人机边缘计算场景下智能分组机制  

Intelligent Grouping Mechanism for UAV-assisted Edge Computing Network in 6G

作　　者：杨思远 梁微 李立欣[1] YANG Siyuan;LIANG Wei;LI Lixin(Northwestern Polytechnical University,Xi'an 710072,China)

机构地区：[1]西北工业大学电子信息学院,陕西西安710072

出　　处：《移动通信》2022年第9期8-13,29,共7页Mobile Communications

基　　金：国家自然科学基金项目(62101450);深圳市科技基础研究(JCYJ20210324121006017);西安电子科技大学国家重点实验室项目(ISN22-03)。

摘　　要：6G网络中无人机应用场景呈现出时间导向型、资源密集型趋势,产生了频谱资源有限、传输时延阈值低等问题。针对这些问题,提出了一种密集无人机协同上行卸载传输网络架构,并在此基础上对无人机集群的分组策略和功率分配问题展开研究。在考虑任务时间阈值限制、无人机功率限制的基础上,建模了以无人机集群整体能效最大化为目标的联合用户分组和功率分配优化问题,并基于联盟型博弈理论提出了一种时间导向的智能博弈分组算法,使无人机群能够自适应地实现分组合作。最终通过仿真证明了该算法的收敛性以及有效性。The application scenarios of UAVs in 6G networks present a time-oriented and resource-intensive trend,resulting in limited spectrum resources and low transmission delay thresholds.To address these problems,a collaborative uplink offloading network architecture for dense UAVs is proposed,and the grouping strategy and power allocation of the UAV swarm are studied on this basis.We aim to maximize the overall energy efficiency of the UAV swarm by jointly optimizing the grouping strategy and power allocation,subject to the constraints of task delay threshold and maximum UAV power.To this end,a time-oriented intelligent grouping algorithm is proposed based on the coalition game theory,which enables the UAV swarm to achieve group cooperation adaptively.Finally,the convergence and effectiveness of the proposed algorithm are proved by simulation results.

关 键 词：无人机 移动边缘计算 博弈论 非正交多址接入 用户分组 

分 类 号：TN929.5[电子电信—通信与信息系统]