国防科技大学学报2023，Vol.45Issue(6)：56-63,8.DOI:10.11887/j.cn.202306008
智能反射面辅助的无线网络加权和速率优化设计
Weighted sum rate optimization for intelligent reflecting surface-aided wireless network
摘要
Abstract
For the transmission design problem in an IRS(intelligent reflecting surface)-enabled network,by jointly designing the transmit beamforming and IRS reflecting coefficient,the goal of this paper was to maximize the weighted sum rate for multiply ground users,subject to the transmit power and the unit modulus constraint.To solve the non-convex objective,we developed an alternating optimization method,where the phase shifter optimization was solved by the RMG(Riemannian manifold gradient)method,and the beamforming was obtained by the bisection search method.Furthermore,an element-wise block coordinate descent-based method was proposed to reduce the complexity of the RMG method.Simulation results verify the effectiveness of the proposed algorithm,and demonstrate that IRS can significantly improve the spectrum efficiency,when the reflecting coefficients are properly optimized.关键词
智能反射面/加权和速率优化/黎曼流形梯度算法/智能元素块坐标下降方法Key words
intelligent reflecting surface/weighted sum rate optimization/Riemannian manifold gradient algorithm/element-wise block coordinate descent method分类
信息技术与安全科学引用本文复制引用
牛和昊,林志,王勇,王磊,赵青松..智能反射面辅助的无线网络加权和速率优化设计[J].国防科技大学学报,2023,45(6):56-63,8.基金项目
国家自然科学基金资助项目(61901490,62201592,61671454) （61901490,62201592,61671454）
中国科协青年人才托举工程资助项目(2021-JCJQ-QT-048) （2021-JCJQ-QT-048）
澳门青年学者计划资助项目(AM2022011) （AM2022011）
国防科技大学科研计划资助项目(ZK21-33) （ZK21-33）
