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.
Highlights
INTRODUCTIONIn our previous work [10], [11], throughput maximization was considered by jointly optimizing the sensing performance, the power allocation, and the U NMANNED aerial vehicle (UAV) positions based on a circular trajectory
U NMANNED aerial vehicle (UAV)-enabled communication is considered as a promising technique to significantly improve the coverage and the performance of terrestrial communication networks
The contributions of our work can be summarized as follows: 1) We extend the communication system based on the probabilistic LoS channel, which approximates the occurrence of LoS and non-LoS (NLoS) channel as a logistic function, while most of the existing works have adopted the channel dominated by the LoS component; 2) The impact of the UAV’s trajectory planning and resource allocation on efficient spectrum sharing is investigated, which reveals some insights for the trade-off between the UAV’s throughput and the interference leakage to the primary receivers (PRs); 3) The corresponding optimization problem turns out to be challenging, which is formulated as a mixed integer nonconvex problem
Summary
In our previous work [10], [11], throughput maximization was considered by jointly optimizing the sensing performance, the power allocation, and the UAV positions based on a circular trajectory. The contributions of our work can be summarized as follows: 1) We extend the communication system based on the probabilistic LoS channel, which approximates the occurrence of LoS and non-LoS (NLoS) channel as a logistic function, while most of the existing works have adopted the channel dominated by the LoS component; 2) The impact of the UAV’s trajectory planning and resource allocation on efficient spectrum sharing is investigated, which reveals some insights for the trade-off between the UAV’s throughput and the interference leakage to the PRs; 3) The corresponding optimization problem turns out to be challenging, which is formulated as a mixed integer nonconvex problem.
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