南京邮电大学学报（自然科学版）2025，Vol.45Issue(3)：28-37,10.DOI:10.14132/j.cnki.1673-5439.2025.03.004
智能反射面辅助的无人机认知网络资源优化算法
A resource optimization algorithm for intelligent reflective surface-assisted UAV cognitive network
摘要
Abstract
The combination of unmanned aerial vehicles(UAVs)and spectrum sharing technology can help to establish high-quality communication links and improve the efficiency of spectrum resource utili-zation.However,due to the existence of cross-links interference between primary and secondary users,it is challenging to achieve high accessibility rates for secondary users.In order to solve this problem,this paper introduces intelligent reflective surface(IRS)and proposes an IRS-assisted UAV cognitive relay communication network paper..The weighted sum rate(WSR)of secondary users in the spectrum shar-ing network is maximized by jointly optimizing the deployment of the UAV,beamforming of the second-ary base station,and the phase shift matrix of IRS.We define it as a non-convex problem and decouple the problem into three sub-problems and then propose an alternating optimization algorithm to iteratively optimize the variables.The UAVs deployment is optimized through the successive convex approximation(SCA)method.The beamforming of the secondary base station is optimized by the direct fractional pro-gramming(DFP)method.The phase shift matrix of IRS is optimized by DFP and the alternating direction method of multipliers(ADMM).Simulation results show that compared with the baseline algorithms,the proposed algorithm can achieve higher secondary users WSR.关键词
无人机/智能反射面/频谱共享/波束成形/加权和速率Key words
unmanned aerial vehicle/intelligent reflective surface(IRS)/spectrum sharing/beamform-ing/weighted sum rate分类
信息技术与安全科学引用本文复制引用
俞荣康,胡晗,杨龙祥..智能反射面辅助的无人机认知网络资源优化算法[J].南京邮电大学学报（自然科学版）,2025,45(3):28-37,10.基金项目
国家自然科学基金(62471254)资助项目 （62471254）
