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An aerial base station (ABS), i.e., unmanned aerial vehicle-mounted base station, has a significant potential to effectively boost the coverage of next-generation wireless networks, having capability of adaptively serving traffic increase in temporary events (i.e., hotspots). However, designing an efficient 3D deployment of ABSs is a considerably complicated problem due to its high degree of freedom and inter-cell interference among ABSs. In this paper, we propose a novel distributed 3D ABS deployment method for providing on-demand downlink communications. To consider the spatial and temporal variations of user locations due to user activities, we model them by an inhomogeneous point process. By analyzing the performance metrics under this model and applying a distributed push-sum, we develop an ABS deployment algorithm with theoretical convergence guarantee that solves the maximization problems of the overall communication quality in a distributed and iterative manner. In our method, each ABS updates its position based on its local information by communicating with its neighboring ABSs. Furthermore, we propose an estimation method of the overall user density from partial observation of ground sensors. Simulation results demonstrate that our method can efficiently improve the overall communication quality and can be applied to a dynamic network.
Kimura et al. (Mon,) studied this question.