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Deep Q-Network Based Dynamic Movement Strategy in a UAV-Assisted Network

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Document pages: 6 pages

Abstract: Unmanned aerial vehicle (UAV)-assisted communications is a promising solutionto improve the performance of future wireless networks, where UAVs are deployedas base stations for enhancing the quality of service (QoS) provided to groundusers when traditional terrestrial base stations are unavailable or notsufficient. An effective framework is proposed in this paper to manage thedynamic movement of multiple unmanned aerial vehicles (UAVs) in response toground user mobility, with the objective to maximize the sum data rate of theground users. First, we discuss the relationship between the air-to-ground(A2G) path loss (PL) and the location of UAVs. Then a deep Q-network (DQN)based method is proposed to adjust the locations of UAVs to maximize the sumdata rate of the user equipment (UE). Finally, simulation results show that theproposed method is capable of adjusting UAV locations in a real-time conditionto improve the QoS of the entire network.

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