Minimum Throughput Maximization for Multi-UAV Enabled WPCN: A Deep Reinforcement Learning Method

Minimum Throughput Maximization for Multi-UAV Enabled WPCN: A Deep Reinforcement Learning Method

This paper investigates joint unmanned aerial vehicle (UAV) trajectory planning and time resource allocation for minimum throughput maximization in a multiple UAV-enabled wireless powered communication network (WPCN). In particular, the UAVs perform as base stations (BS) to broadcast energy signals...

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Bibliographic Details
Main Authors: Jie Tang, Jingru Song, Junhui Ou, Jingci Luo, Xiuyin Zhang, Kai-Kit Wong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Unmanned aerial vehicle (UAV)
wireless powered communication network (WPCN)
Internet of Things (IoT)
trajectory design
deep reinforcement learning (DRL)
Online Access:https://ieeexplore.ieee.org/document/8950047/

Internet

https://ieeexplore.ieee.org/document/8950047/

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