摘要
针对无人机(UAV)通信网络中频谱资源紧缺的问题,构建基于认知无线电的多无人机通信网络,通过多机协作频谱感知有效探索授权频谱。提出一种基于Bisection算法的迭代算法,通过联合优化感知时间和判决门限对构建的复杂非凸问题求解,显著提高了无人机次级认知网络的能量效率(EE)。分析了无人机飞行过程中能效的变化情况,仿真结果表明,存在最优感知时间使能效获得最大值,且判决门限的选择会影响该能效最优值;提出的高能效迭代算法具有较好收敛性,有效提高了认知无人机网络的能量利用率。
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.
作者
张宏伟
达新宇
胡航
倪磊
潘钰
ZHANG Hongwei;DA Xinyu;HU Hang;NI Lei;PAN Yu(Graduate School,Air Force Engineering University,Xi'an 710077,China;College of Artificial Intelligence,Yango University,Fuzhou 350015,China;Information and Navigation College,Air Force Engineering University,Xi'an 710077,China)
出处
《航空学报》
EI
CAS
CSCD
北大核心
2021年第6期519-529,共11页
Acta Aeronautica et Astronautica Sinica
基金
国家自然科学基金(61901509)
博士后创新人才计划(BX201700108)
空军工程大学校长基金(XZJK2019033)
空军工程大学信息与导航学院创新基金(YNLX1904025)。
关键词
协作频谱感知
无人机(UAV)
认知无线电
能量效率(EE)
凸优化
cooperative spectrum sensing
Unmanned Air Vehicles(UAV)
cognitive radio
Energy Efficiency(EE)
convex optimization
