Deep Reinforcement Learning Evolution Algorithm for Dynamic Antenna Control in Multi-Cell Configuration HAPS System

Deep Reinforcement Learning Evolution Algorithm for Dynamic Antenna Control in Multi-Cell Configuration HAPS System

In this paper, we propose a novel Deep Reinforcement Learning Evolution Algorithm (DRLEA) method to control the antenna parameters of the High-Altitude Platform Station (HAPS) mobile to reduce the number of low-throughput users. Considering the random movement of the HAPS caused by the winds, the th...

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Bibliographic Details
Main Authors: Siyuan Yang, Mondher Bouazizi, Tomoaki Ohtsuki, Yohei Shibata, Wataru Takabatake, Kenji Hoshino, Atsushi Nagate
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Future Internet
Subjects:
HAPS
antenna control
reinforcement learning
evolution algorithm
Online Access:https://www.mdpi.com/1999-5903/15/1/34

Internet

https://www.mdpi.com/1999-5903/15/1/34

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