Unmanned Aerial Vehicle (UAV)

Enabled Wireless Communications and Networking

Edited by
July 2022
264 pages
  • ISBN978-3-0365-4663-6 (Hardback)
  • ISBN978-3-0365-4664-3 (PDF)

This book is a reprint of the Special Issue Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking that was published in

Chemistry & Materials Science
Environmental & Earth Sciences

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.

  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
unmanned aerial vehicle; UAV positioning; machine learning; wireless communications; drones; network; DTN; mobility schedule; routing algorithms; data delivery; Internet of drones; communication; security; privacy; UAV base station; MIMO; millimeter-wave band; blind beamforming; signal recovery; UAV relay networks; UAV positioning; resource management; transmit time allocation; unmanned aerial vehicles; dynamic spectrum access; quality of service; reinforcement learning; multi-armed bandit; aerial communication; FANET; not-spots; stratospheric communication platform; UAV; UAV-assisted network; 5G; unmanned aerial vehicles; global positioning system; GPS spoofing attacks; detection techniques; machine learning; dynamic selection; hyperparameter tuning; IoT; RF radio communication; Wi-Fi direct; D2D; drone-based mobile secure zone; friendly jamming; mobility; internet of things; non-orthogonal multiple access; resource allocation; ultra reliable low latency communication; unmanned aerial vehicles; uplink transmission; Deep Q-learning (DQL); Double Deep Q-learning (DDQL); dynamic spectrum sharing; High Altitude Platform Station (HAPS); cellular communications; power control; interference management; cognitive UAV networks; clustered two-stage-fusion cooperative spectrum sensing; continuous hidden Markov model; SNR estimation; n/a

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