Energy Aware Multiarmed Bandit for Millimeter Wave-Based UAV Mounted RIS Networks

Ehab Mahmoud Mohamed, Sherief Hashima, Kohei Hatano

研究成果: ジャーナルへの寄稿学術誌査読

5 被引用数 (Scopus)


Reconfigurable intelligent surface (RIS) and unmanned aerial vehicle (UAV) are anticipated as talented technologies to extend the range of millimeter wave (mmWave) communications. In this letter, a UAV equipped with RIS (UAV-RIS) is used to assist mmWave base station (BS) in covering users in hotspot areas. In this context, UAV should cover several high-capacity hotspots while minimizing its flying/hovering energy consumptions. Energy-aware multi-armed bandit (EA-MAB) algorithm is proposed as an effective online learning tool to handle this problem efficiently. By which, the UAV acts as the player trying to maximize its achievable rate, i.e., the reward, over selecting different hotspots in its trajectory, i.e., the arms of the bandit game. This is done while minimizing the energy/cost of the UAV flight from one hotspot to another over the time span of its battery life. Numerical analysis confirms the superior performance of the proposed EA-MAB algorithm over benchmarks.

ジャーナルIEEE Wireless Communications Letters
出版ステータス出版済み - 6月 1 2022

!!!All Science Journal Classification (ASJC) codes

  • 制御およびシステム工学
  • 電子工学および電気工学


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