智能反射面辅助的无线网络加权和速率优化设计*
作者:
作者单位:

1.国防科技大学 电子对抗学院;2.国防科技大学 电子制约技术安徽省重点实验室

作者简介:

牛和昊 (1988—),男,安徽芜湖人,讲师,博士, Email:niuhaonupt@foxmail.com;

通讯作者:

林志 ,男,安徽池州人,副教授,博士,硕士生导师, Email:linzhi@nudt.edu.cn

中图分类号:

TN92

基金项目:

国家自然科学基金资助项目(61901490,62201592,61671454) ; 中国科协青年人才托举工程资助项目(2021-JCJQ-QT-048) ; 澳门青年学者计划资助项目(AM2022011) ; 国防科技大学科研计划资助项目(ZK21-33)


Weighted sum rate optimization for intelligent reflecting surface-aided wireless network
Author:
Affiliation:

1.Colloge of Electronic Engineering, National University of Defense Technology, Hefei 230037 , China;2.Anhui Province Key Laboratory of Electronic Restriction, National University of Defense Technology, Hefei 230037 , China

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    摘要:

    针对智能反射面(intelligent reflecting surface,IRS)辅助的无线网络传输设计的目标是通过联合设计基站处的发送波束形成向量和IRS的反射系数,在满足基站发射功率和IRS单位模约束的条件下,使多个地面用户的加权和速率最大化。为了求解非凸的目标函数,提出一种交替优化方法,其中采用黎曼流形梯度(Riemannian manifold gradient,RMG)方法来优化反射系数,使用二分搜索法优化发送波束形成向量。此外,为了降低RMG方法的复杂度,设计了一种智能元素块坐标下降方法。仿真结果验证了所提算法的有效性,并且表明通过优化设计反射系数,IRS可显著提高无线网络的频谱效率。

    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.

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引用本文

牛和昊,林志,王勇,等.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.
NIU Hehao, LIN Zhi, WANG Yong, et al. Weighted sum rate optimization for intelligent reflecting surface-aided wireless network[J]. Journal of National University of Defense Technology,2023,45(6):56-63.

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  • 收稿日期:2022-04-10
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  • 在线发布日期: 2024-11-27
  • 出版日期: 2023-12-28
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