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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語言:英语
出版: MDPI - Multidisciplinary Digital Publishing Institute 2022
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collection Directory of Open Access Books
description 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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institution Directory of Open Access Books
language eng
publishDate 2022
publishDateRange 2022
publishDateSort 2022
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-911272024-04-11T15:11:02Z Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking Deruyck, Margot 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 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 global positioning system GPS spoofing attacks detection techniques 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 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology 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. 2022-08-12T12:43:17Z 2022-08-12T12:43:17Z 2022 book ONIX_20220812_9783036546636_6 9783036546636 9783036546643 https://directory.doabooks.org/handle/20.500.12854/91127 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5760 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4664-3 10.3390/books978-3-0365-4664-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036546636 9783036546643 264 Basel open access
spellingShingle 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
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
global positioning system
GPS spoofing attacks
detection techniques
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
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
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title_full Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title_fullStr Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title_full_unstemmed Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title_short Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking
title_sort unmanned aerial vehicle uav enabled wireless communications and networking
topic 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
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
global positioning system
GPS spoofing attacks
detection techniques
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
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
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet 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
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
global positioning system
GPS spoofing attacks
detection techniques
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
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
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url ONIX_20220812_9783036546636_6