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UAV-Assisted Secure Communications in Terrestrial Cognitive Radio Networks: Joint Power Control and 3D Trajectory Optimization

Authors
Nguyen, P.X.Nguyen, V.Nguyen, H.V.Shin, O.
Issue Date
Apr-2021
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Cognitive radio; Cognitive radio networks; inner approximation; Interference; Jamming; physical layer security; Radio transmitters; Receivers; Three-dimensional displays; trajectory optimization; unmanned aerial vehicles; Unmanned aerial vehicles
Citation
IEEE Transactions on Vehicular Technology, v.70, no.4, pp.3298 - 3313
Journal Title
IEEE Transactions on Vehicular Technology
Volume
70
Number
4
Start Page
3298
End Page
3313
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/40719
DOI
10.1109/TVT.2021.3062283
ISSN
0018-9545
Abstract
This paper considers secure communications for an underlay cognitive radio network (CRN) in the presence of an external eavesdropper (Eve). The secrecy performance of CRNs is usually limited by the primary receiver's interference power constraint. To overcome this issue, we propose to use an unmanned aerial vehicle (UAV) as a friendly jammer to interfere Eve in decoding the confidential message from the secondary transmitter. Our goal is to jointly optimize the transmit power and UAV's trajectory in the three-dimensional space to maximize the average achievable secrecy rate of the secondary system. The formulated optimization problem is nonconvex due to the nonconvexity of the objective and non-convexity of constraints, which is very challenging to solve. To obtain a suboptimal but efficient solution to the problem, we first transform the original problem into a more tractable form and develop an iterative algorithm for its solution by leveraging the inner approximation (IA) framework. Combining tools from IA framework and S-procedure, we further extend the proposed algorithm to a more realistic scenario, where the imperfect location information of ground nodes (including Eve, secondary receiver and primary receiver) is considered, resulting in the average worst-case secrecy rate. Extensive numerical results are provided to demonstrate the merits of the proposed algorithms over existing approaches. IEEE
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College of Information Technology (Department of IT Convergence)
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