Learning-Aided Realtime Performance Optimisation of Cognitive UAV-Assisted Disaster Communication

Trung Q. Duong, Long D. Nguyen, Hoang Duong Tuan, Lajos Hanzo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this work, we propose efficient optimisation methods for relay-assisted unmanned aerial vehicles (UAVs) in cognitive radio networks (CRNs) to cope with the network destruction in the event of a natural disaster. Our model considers real- time optimisation in embedded UAV-CRN communication involved in recovering wireless communication services. Particularly, by conceiving advanced optimisation techniques and training deep neural networks, our solutions become capable of supporting real-time applications in disaster recovery scenarios. Our algorithms impose low computational complexity, hence, have a low execution time in solving real- time optimisation problems. Numerical results demonstrate the benefits of our approaches proposed for UAV-CRN
Original languageEnglish
Title of host publicationIEEE IEEE Global Communications Conference 2019 (GLOBECOM 2019)
Publisher IEEE
DOIs
Publication statusPublished - 27 Feb 2020

Publication series

NameIEEE Global Communications Conference (GLOBECOM): Proceedings
PublisherIEEE
ISSN (Electronic)2576-6813

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