Deploying UAV Base Stations in Communication Network Using Machine Learning
Date
2019-12-21
Authors
Zhong, Xukai
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Abstract
Today has witnessed a constantly increasing demand for high-quality wireless
communications services. Moreover, the quality of service (QoS) requirement of future
5G and beyond cellular networks leads to the possible use of the unmanned aerial
vehicle base station (UAV-BS). Deploying UAV-BSs to assist the communications
network has become a research direction with great potential. In this project, we focus
on the problem of deploying UAV-BSs to provide satisfactory wireless communication
services, with the aim that maximizes the total number of covered user equipment
subject to user data rate requirements and UAV-BS capacity limit. Then, the report
extends to a reinforcement learning based method to adjust the locations of UAVs
to maximize the sum data rate of the user equipment (UE). Numerical experiments
under practical settings provide supportive evidences to our design.
Description
Keywords
Unmanned Aerial Vehicle, Machine Learning, Reinforcement Learning, Optimization, Genetic Algorithm