Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly c...

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Bibliographic Details
Other Authors: Deruyck, Margot (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
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DOAB: description of the publication
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245 1 0 |a Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking 
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520 |a The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network's infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out. 
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546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
650 7 |a History of engineering & technology  |2 bicssc 
653 |a unmanned aerial vehicle 
653 |a UAV positioning 
653 |a machine learning 
653 |a wireless communications 
653 |a drones 
653 |a network 
653 |a DTN 
653 |a mobility schedule 
653 |a routing algorithms 
653 |a data delivery 
653 |a Internet of drones 
653 |a communication 
653 |a security 
653 |a privacy 
653 |a UAV base station 
653 |a MIMO 
653 |a millimeter-wave band 
653 |a blind beamforming 
653 |a signal recovery 
653 |a UAV relay networks 
653 |a resource management 
653 |a transmit time allocation 
653 |a unmanned aerial vehicles 
653 |a dynamic spectrum access 
653 |a quality of service 
653 |a reinforcement learning 
653 |a multi-armed bandit 
653 |a aerial communication 
653 |a FANET 
653 |a not-spots 
653 |a stratospheric communication platform 
653 |a UAV 
653 |a UAV-assisted network 
653 |a 5G 
653 |a global positioning system 
653 |a GPS spoofing attacks 
653 |a detection techniques 
653 |a dynamic selection 
653 |a hyperparameter tuning 
653 |a IoT 
653 |a RF radio communication 
653 |a Wi-Fi direct 
653 |a D2D 
653 |a drone-based mobile secure zone 
653 |a friendly jamming 
653 |a mobility 
653 |a internet of things 
653 |a non-orthogonal multiple access 
653 |a resource allocation 
653 |a ultra reliable low latency communication 
653 |a uplink transmission 
653 |a Deep Q-learning (DQL) 
653 |a Double Deep Q-learning (DDQL) 
653 |a dynamic spectrum sharing 
653 |a High Altitude Platform Station (HAPS) 
653 |a cellular communications 
653 |a power control 
653 |a interference management 
653 |a cognitive UAV networks 
653 |a clustered two-stage-fusion cooperative spectrum sensing 
653 |a continuous hidden Markov model 
653 |a SNR estimation 
653 |a n/a 
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