Energy-Efficiency Optimization of UAV-Based Cognitive Radio System

• Published in: IEEE access Vol. 7; pp. 155381 - 155391
• Main Authors: Pan, Yu, Da, Xinyu, Hu, Hang, Zhu, Zhengyu, Xu, Ruiyang, Ni, Lei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cognitive radio; cognitive radio (CR) network; Computational geometry; Convexity; Data communication; Data transmission; Energy consumption; energy efficiency; Energy management; Miniaturization; opportunistic spectrum access (OSA); Optimization; Particle swarm optimization; Performance enhancement; Quality of service; Sensors; spectrum sensing; Unmanned aerial vehicle (UAV); Unmanned aerial vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2939616

Unmanned aerial vehicles (UAVs) equipped with data transmission and sensing facilities are gaining more popularity in different applications due to its miniaturization and mobility. In this paper, a UAV-based overlay cognitive radio (CR) network is investigated in which the UAV is used as a secondary user (SU). This paper proposes an efficient energy management solution to improve the performance of the UAV. When SUs opportunistically utilize the licensed spectrum of the primary network, spectrum sensing is needed to determine whether to transmit data or not, so the sensing time and secondary transmission power should be jointly optimized. We formulate this non-convex optimization problem subject to multiple constraints, which seeks to investigate on the effect of the sensing time and transmission power on the performance of the system. The problem is difficult to tackle, then we propose an algorithm applying the techniques of alternating optimization and dichotomy method. In addition, we compare the proposed algorithm with the particle swarm optimization (PSO) algorithm to verify its performance. Numerical results show that our proposed algorithm outperforms the PSO algorithm and significantly enhances the energy efficiency of the UAV-based CR system.