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Due to the high maneuverability of unmanned aerial vehicle (UAV), a cluster of UAVs is considered used to collect sensing data from the sensors that distributed randomly in an area without the terrestrial infrastructure. The cluster members work as relays to forward the sensing data from sensors to the cluster head. For the reason that the relay deployment impacts the transmission rate and coverage area directly, we are going to optimize the deployment of the UAV relays, aiming to maximize the total capacity of the network. The problem of multi-relay deployment is intractable for two reasons. On one hand, because of the interactional and coupled relationship among the UAV relays, when the deployment of any given relay changes, the deployment optimization of other relays will be affected. On the other hand, on account of that the exact positions of the sensors are unknown, the deployment optimization of the UAV relays cannot be completed directly because of lacking parameters. In order to tackle the coupled relationship among the UAV relays, the problem of multi-relay deployment is modeled as a local interaction game. We prove that the multi-relay deployment game is an exact potential game that has at least one Nash equilibrium (NE) point. Then, the better reply-based relay deployment approach, which is an online learning approach that does not demand the information of the exact positions of sensors, is proposed to search the NE point. The simulation results show that the network capacity is significantly enhanced with the proposed relays deployment approach.

Deployment Optimization of UAV Relays for Collecting Data From Sensors: A Potential Game Approach