On the Application of Machine Learning to the Design of UAV-Based 5G Radio Access Networks

On the Application of Machine Learning to the Design of UAV-Based 5G Radio Access Networks

A groundbreaking design of radio access networks (RANs) is needed to fulfill 5G traffic requirements. To this aim, a cost-effective and flexible strategy consists of complementing terrestrial RANs with unmanned aerial vehicles (UAVs). However, several problems must be solved in order to effectively...

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Bibliographic Details
Main Authors: Vahid Kouhdaragh, Francesco Verde, Giacinto Gelli, Jamshid Abouei
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Electronics
Subjects:
5G and beyond systems
machine learning
radio access networks
reinforcement learning
supervised learning
unmanned aerial vehicles (UAVs)
Online Access:https://www.mdpi.com/2079-9292/9/4/689

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https://www.mdpi.com/2079-9292/9/4/689

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