Unmanned aerial vehicle (UAV) communications have been widely accepted as promising technologies to support air-to-ground communications in the forthcoming sixth-generation (6G) wireless networks. This paper proposes a novel air-to-ground communication model consisting of aerial base stations served by UAVs and terrestrial user equipments (UEs) by integrating the technique of coordinated multi-point (CoMP) transmission with the theory of stochastic geometry. In particular, a CoMP set consisting of multiple UAVs is developed based on the theory of Poisson-Delaunay tetrahedralization. Effective UAV formation control and UAV swarm tracking schemes for two typical scenarios, including static and mobile UEs, are also developed using the multi-agent system theory to ensure that collaborative UAVs can efficiently reach target spatial positions for mission execution. Thanks to the ease of mathematical tractability, this model provides explicit performance expressions for a typical UE's coverage probability and achievable ergodic rate. Extensive simulation and numerical results corroborate that the proposed scheme outperforms UAV communications without CoMP transmission and obtains similar performance to the conventional CoMP scheme while avoiding search overhead.

翻译：无人机通信已被广泛视为支持未来第六代（6G）无线网络中空对地通信的 promising 技术。本文通过将协调多点（CoMP）传输技术与随机几何理论相结合，提出了一种新型空对地通信模型，该模型包含由无人机服务的空中基站和地面用户设备（UE）。具体而言，基于泊松-德劳内四面体化理论，构建了一个由多架无人机组成的CoMP集合。针对静态UE和移动UE两种典型场景，还利用多智能体系统理论开发了有效的无人机编队控制与无人机集群追踪方案，以确保协作无人机能够高效到达目标空间位置以执行任务。得益于数学易处理性，该模型给出了典型UE覆盖概率和可达遍历速率的显式性能表达式。大量仿真与数值结果证实，所提方案在性能上优于无CoMP传输的无人机通信，且与传统CoMP方案性能相近，同时避免了搜索开销。