arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2202.02457cs.NIeess.SP
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Path Planning for the Dynamic UAV-Aided Wireless Systems using Monte Carlo Tree Search

Yuwen Qian, Kexin Sheng, Chuan Ma, Jun Li, Ming Ding, Mahbub Hassan

英文摘要:

For UAV-aided wireless systems, online path planning attracts much attention recently. To better adapt to the real-time dynamic environment, we, for the first time, propose a Monte Carlo Tree Search (MCTS)-based path planning scheme. In details, we consider a single UAV acts as a mobile server to provide computation tasks offloading services for a set of mobile users on the ground, where the movement of ground users follows a Random Way Point model. Our model aims at maximizing the average throughput under energy consumption and user fairness constraints, and the proposed timesaving MCTS algorithm can further improve the performance. Simulation results show that the proposed algorithm achieves a larger average throughput and a faster convergence performance compared with the baseline algorithms of Q-learning and Deep Q-Network.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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