[1]
|
An Overview of Cognitive Radio Technology and Its Applications in Civil Aviation
Sensors,
2023
DOI:10.3390/s23136125
|
|
|
[2]
|
QoS-Dependent Event-Triggered Control for UAVs on Cognitive Radio Networks Subject to Deception Attacks
IEEE Transactions on Vehicular Technology,
2023
DOI:10.1109/TVT.2023.3271326
|
|
|
[3]
|
Dynamic Spectrum Management with Network Function Virtualization for UAV Communication
Journal of Intelligent & Robotic Systems,
2021
DOI:10.1007/s10846-021-01318-0
|
|
|
[4]
|
Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication
Sensors,
2021
DOI:10.3390/s21020534
|
|
|
[5]
|
Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication
Sensors,
2021
DOI:10.3390/s21020534
|
|
|
[6]
|
Dynamic Spectrum Management with Network Function Virtualization for UAV Communication
Journal of Intelligent & Robotic Systems,
2021
DOI:10.1007/s10846-021-01318-0
|
|
|
[7]
|
A Survey of Cyberattack Countermeasures for Unmanned Aerial Vehicles
IEEE Access,
2021
DOI:10.1109/ACCESS.2021.3124996
|
|
|
[8]
|
A Switching Method to Event-Triggered Output Feedback Control for Unmanned Aerial Vehicles Over Cognitive Radio Networks
IEEE Transactions on Systems, Man, and Cybernetics: Systems,
2021
DOI:10.1109/TSMC.2020.2971726
|
|
|
[9]
|
Performance Comparison of Machine Learning Algorithms in Detecting Jamming Attacks on ADS-B0 Devices
2019 IEEE International Conference on Electro Information Technology (EIT),
2019
DOI:10.1109/EIT.2019.8833789
|
|
|
[10]
|
Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey and Future Directions
IEEE Communications Surveys & Tutorials,
2019
DOI:10.1109/COMST.2019.2924143
|
|
|
[11]
|
Cyber-attacks on unmanned aerial system networks: Detection, countermeasure, and future research directions
Computers & Security,
2019
DOI:10.1016/j.cose.2019.05.003
|
|
|
[12]
|
Integration of a radar sensor into a sense-and-avoid payload for small UAS
2018 IEEE Aerospace Conference,
2018
DOI:10.1109/AERO.2018.8396609
|
|
|
[13]
|
Analysis of vulnerabilities, attacks, countermeasures and overall risk of the Automatic Dependent Surveillance-Broadcast (ADS-B) system
International Journal of Critical Infrastructure Protection,
2017
DOI:10.1016/j.ijcip.2017.10.002
|
|
|
[14]
|
Techniques for dealing with uncertainty in cognitive radio networks
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC),
2017
DOI:10.1109/CCWC.2017.7868352
|
|
|
[15]
|
Energy efficient 3D positioning of micro unmanned aerial vehicles for underlay cognitive radio systems
2017 IEEE International Conference on Communications (ICC),
2017
DOI:10.1109/ICC.2017.7996485
|
|
|
[16]
|
Energy-Efficient Management of Unmanned Aerial Vehicles for Underlay Cognitive Radio Systems
IEEE Transactions on Green Communications and Networking,
2017
DOI:10.1109/TGCN.2017.2750721
|
|
|
[17]
|
A spectrum sensing technique based on autocorrelation and Euclidean distance and its comparison with energy detection for cognitive radio networks
Computers & Electrical Engineering,
2016
DOI:10.1016/j.compeleceng.2015.05.015
|
|
|
[18]
|
Cognitive Radio for Aeronautical Communications: A Survey
IEEE Access,
2016
DOI:10.1109/ACCESS.2016.2570802
|
|
|
[19]
|
A spectrum sensing technique based on autocorrelation and Euclidean distance and its comparison with energy detection for cognitive radio networks
Computers & Electrical Engineering,
2016
DOI:10.1016/j.compeleceng.2015.05.015
|
|
|
[20]
|
A spectrum sensing technique based on autocorrelation and Euclidean distance and its comparison with energy detection for cognitive radio networks
Computers & Electrical Engineering,
2016
DOI:10.1016/j.compeleceng.2015.05.015
|
|
|
[21]
|
A spectrum sensing technique based on autocorrelation and Euclidean distance and its comparison with energy detection for cognitive radio networks
Computers & Electrical Engineering,
2016
DOI:10.1016/j.compeleceng.2015.05.015
|
|
|
[22]
|
Integration of Cognitive Radio Technology with unmanned aerial vehicles: Issues, opportunities, and future research challenges
Journal of Network and Computer Applications,
2015
DOI:10.1016/j.jnca.2014.12.002
|
|
|
[23]
|
A Bayesian network model of the bit error rate for cognitive radio networks
2015 IEEE 16th Annual Wireless and Microwave Technology Conference (WAMICON),
2015
DOI:10.1109/WAMICON.2015.7120377
|
|
|