Paper Info
Title
Joint Optimization of Trajectory and Resource Allocation for Time-Constrained UAV-Enabled Cognitive Radio Networks
Abstract
Unmanned aerial vehicle (UAV)-enabled communication has emerged as an irreplaceable technology in military, disaster relief and emergency scenarios. This correspondence investigates the average throughput in a UAV-enabled cognitive radio network, where the UAV is regarded as a dedicated secondary user to enhance the network coverage and spectral efficiency. Based on the probabilistic line-of-sight channel, we exploit the joint design of UAV trajectory and resource allocation to maximize the average throughput under the constraints of co-channel interference and completion time. The original problem is a mixed integer non-convex problem which is generally NP-hard. We first decompose the primal problem into a bilevel programming problem, and then propose an efficient high-quality algorithm based on the particle swarm optimization approach. The optimized trajectory reveals the trade-off between throughput and co-channel interference. Numerical results verify the superiority of the proposed algorithm as compared to other benchmark schemes.
Year
DOI
Venue
2022
10.1109/TVT.2022.3151671
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
Cognitive radio network,unmanned aerial vehicle (UAV) communication,trajectory design,throughput maximization
Journal
71
Issue
ISSN
Citations 
5
0018-9545
0
PageRank 
References 
Authors
0.34
15
7
Name
Order
Citations
PageRank
Yu Pan100.34
Xinyu Da233.07
Hang Hu311.03
YangChao Huang434.10
Miao Zhang500.34
Kanapathippillai Cumanan600.34
Octavia A. Dobre72064181.08