Electronics and Electrical Engineering and Control

Energy-efficient cooperative optimization for multi-UAV-aided cognitive radio networks

  • ZHANG Hongwei ,
  • DA Xinyu ,
  • HU Hang ,
  • NI Lei ,
  • PAN Yu
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  • 1. Graduate School, Air Force Engineering University, Xi'an 710077, China;
    2. College of Artificial Intelligence, Yango University, Fuzhou 350015, China;
    3. Information and Navigation College, Air Force Engineering University, Xi'an 710077, China

Received date: 2020-07-16

  Revised date: 2020-08-28

  Online published: 2020-09-02

Supported by

National Natural Science Foundation of China (61901509); National Postdoctoral Program for Innovative Talents (BX201700108); The President Foundation of Air Force Engineering University (XZJK2019033); The Innovation Foundation of Air Force Engineering University (YNLX1904025)

Abstract

Aiming at the shortage of spectrum resources in Unmanned Air Vehicle (UAV) communication networks, we construct a multi-UAV communication network model based on cognitive radio, and explore the authorized spectrum effectively through cooperative spectrum sensing. An iterative algorithm based on the bisection algorithm is proposed, and the Energy Efficiency (EE) of UAV secondary cognitive networks is significantly improved by jointly optimizing the sensing time and decision threshold to solve the complex nonconvex problem. Finally, the change of EE in the flight course of UAVs is analyzed. The simulation results show that there is an optimal sensing time to maximize the EE, and that the selection of the decision threshold will affect the optimal value of the EE; with good convergence, the proposed EE iterative algorithm effectively improves the energy utilization of cognitive UAV networks.

Cite this article

ZHANG Hongwei , DA Xinyu , HU Hang , NI Lei , PAN Yu . Energy-efficient cooperative optimization for multi-UAV-aided cognitive radio networks[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021 , 42(6) : 324548 -324548 . DOI: 10.7527/S1000-6893.2020.24548

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