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Spectrum-Sharing UAV-Assisted Mission-Critical Communication: Learning-Aided Real-Time Optimisation
- Source :
- IEEE Access, Vol 9, Pp 11622-11632 (2021), Nguyen, M-H T, Garcia-Palacios, E, Nguyen, L D, Do-Duy, T, Mai, S T & Duong, T Q 2021, ' Spectrum-Sharing UAV-assisted Mission-Critical Communication: Learning-aided Real-time Optimisation ', IEEE Access, vol. 9, pp. 11622-11632 .
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- We propose an unmanned aerial vehicle (UAV) communications scheme with spectrum-sharing mechanism to provide mission-critical services such as disaster recovery and public safety. Specifically, the UAVs can serve as flying base stations to provide extended network coverage for the affected area under spectrum-sharing cognitive radio networks (CRNs). To cope with the effects of network destruction in a disaster, we propose a real-time optimisation framework for resource allocation (e.g., power and number of UAVs) for CRNs assisted by UAV relays. The proposed optimisation scheme aims at optimising the network throughput of primary and secondary networks under the stringent constraint of maximum tolerable interference impinged on the primary users. We also propose a deep neural network (DNN) model to significantly reduce the execution time under real-time solution of mixed-integer UAV deployment problems. For both primary and secondary networks, our real-time optimisation algorithms impose low computational complexity, hence, have a low execution time in solving throughput optimisation problems, which demonstrates the benefit of our approached proposed for spectrum-sharing UAV-assisted mission-critical services.
- Subjects :
- General Computer Science
Computer science
Distributed computing
Mission critical
050801 communication & media studies
Throughput
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
Base station
0508 media and communications
unmanned aerial vehicle (UAV)
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Resource management
Artificial neural network
05 social sciences
General Engineering
Disaster recovery
020206 networking & telecommunications
Cognitive radio
machine learning
Resource allocation
lcsh:Electrical engineering. Electronics. Nuclear engineering
Real-time optimisation
lcsh:TK1-9971
spectrum sharing
mission-critical communications
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....ed552faafd9418b3de50c3e76d1284a8