A Hierarchical Deep Reinforcement Learning Approach for Throughput Maximization in Reconfigurable Intelligent Surface-Aided Unmanned Aerial Vehicle–Integrated Sensing and Communication Network

A Hierarchical Deep Reinforcement Learning Approach for Throughput Maximization in Reconfigurable Intelligent Surface-Aided Unmanned Aerial Vehicle–Integrated Sensing and Communication Network

Integrated sensing and communication (ISAC) is considered a key technology supporting Beyond-5G/6G (B5G/6G) networks, which allows the spectrum resources to be used for both sensing and communication. In this paper, we investigate an unmanned aerial vehicle (UAV)-enabled ISAC scenario, where the UAV...

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Bibliographic Details
Main Authors: Haitao Chen, Jiansong Miao, Ruisong Wang, Hao Li, Xiaodan Zhang
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Drones
Subjects:
integrated sensing and communication (ISAC)
unmanned aerial vehicle (UAV)
reconfigurable intelligent surface (RIS)
hierarchical deep reinforcement learning (HDRL)
Online Access:https://www.mdpi.com/2504-446X/8/12/717

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https://www.mdpi.com/2504-446X/8/12/717

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