Deep Reinforcement Learning for Joint Trajectory Planning, Transmission Scheduling, and Access Control in UAV-Assisted Wireless Sensor Networks

Deep Reinforcement Learning for Joint Trajectory Planning, Transmission Scheduling, and Access Control in UAV-Assisted Wireless Sensor Networks

Unmanned aerial vehicles (UAVs) can be used to relay sensing information and computational workloads from ground users (GUs) to a remote base station (RBS) for further processing. In this paper, we employ multiple UAVs to assist with the collection of sensing information in a terrestrial wireless se...

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Bibliographic Details
Main Authors: Xiaoling Luo, Che Chen, Chunnian Zeng, Chengtao Li, Jing Xu, Shimin Gong
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Sensors
Subjects:
UAV
multi-agent deep reinforcement learning
trajectory planning
access control
Online Access:https://www.mdpi.com/1424-8220/23/10/4691

Internet

https://www.mdpi.com/1424-8220/23/10/4691

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