In this study, the air–ground integrated deployment method is studied for the unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) system. The UAV can help to reduce the delay and energy consumption of MEC. However, the limited coverage range of UAV limits the quality of data offloading. To improve the efficiency of data transmission, a hierarchical game model is designed. Ground nodes form multiple coalitions actively according to the position of UAV and the UAV adjusts the position based on the data distribution of ground networks. The relationship between the UAV and ground nodes is modelled as a Stackelberg game. A coalition formation game (CFG) is constructed for the data gathering among ground nodes. It is proved that the proposed CFG is an exact potential game with at least one Nash equilibrium. Moreover, the property of Stackelberg equilibrium is proven for the air–ground cooperative relationship. Based on the hierarchical model, a distributed air–ground integrated deployment algorithm is proposed to jointly optimise the position of the UAV and the coalition formation of ground nodes. The simulation results show that the proposed method promotes the efficiency of data transmission greatly and can converge to a stable state with reasonable iteration times.

中文翻译：

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用于支持无人机的移动边缘计算的空地集成部署：分层游戏方法

在这项研究中，研究了空地一体化部署方法，用于支持无人机（UAV）的移动边缘计算（MEC）系统。无人机可以帮助减少MEC的延迟和能耗。但是，无人机的有限覆盖范围限制了数据卸载的质量。为了提高数据传输的效率，设计了一个分层的游戏模型。地面节点根据无人机的位置主动组成多个联盟，无人机根据地面网络的数据分布调整位置。无人机和地面节点之间的关系被建模为Stackelberg游戏。构建了一个联盟形成游戏（CFG），用于在地面节点之间收集数据。事实证明，提出的CFG是具有至少一个Nash平衡的精确潜在博弈。此外，空中-地面合作关系证明了斯塔克尔伯格平衡的性质。基于层次模型，提出了一种分布式空地综合部署算法，以联合优化无人机的位置和地面节点的联合形成。仿真结果表明，该方法大大提高了数据传输效率，并且可以在合理的迭代时间内收敛到稳定状态。