摘要
针对智能反射面(IRS)辅助的下行多用户多输入单输出(MISO)系统,该文以最大化系统频谱效率为目标,在满足基站发射功率和IRS反射单元模约束的条件下,设计基站处主动波束成形向量和IRS的相移矩阵。首先为了实现更高的波束形成自由度,采用了基于空间时间块编码(STBC)的秩二波束形成方案。随后为了求解非凸深度耦合的优化问题,提出了一种交替优化算法。针对IRS相移矩阵的求解,提出了一种改进的黎曼流形共轭梯度法(IRMG)进行优化,同时使用加权最小均方误差(WMMSE)设计主动波束形成向量。仿真结果验证了所提算法具有更快的收敛速度,同时能有效提升系统频谱效率。
Objective To address the limitations of current optimization methods for Intelligent Reflecting Surface(IRS)-aided communication systems—such as high computational complexity,lack of closed-form solutions,and realtime transmission constraints—this study proposes an efficient joint active-passive beamforming algorithm to improve spectral efficiency and real-time performance.As the number of users increases,conventional rank-1 beamforming lacks sufficient design flexibility,highlighting the need for advanced approaches to avoid performance bottlenecks.This challenge is central to the practical deployment of large-scale Multiple-Input Single-Output(MISO)systems.Methods A hierarchical optimization framework is proposed to resolve the non-convex design problem in IRSassisted MISO systems.A joint beamforming model is developed for downlink multi-user scenarios,incorporating Alamouti Space–Time Block Coding(STBC)and rank-2 beamforming to maximize the Weighted Sum Rate(WSR)under total power and IRS unit modulus constraints.The framework jointly optimizes the transmit and reflection matrices to improve spectral efficiency.To address the non-convexity of the formulation,an alternating optimization strategy is adopted.At the base station,a Weighted Minimum Mean-Square Error(WMMSE)algorithm is applied to refine the rank-2 beamforming design,and ensure efficient power allocation.For IRS phase shift optimization,an improved Riemannian Gradient Algorithm(RGA)is proposed.This algorithm integrates restart mechanisms and dynamic scaling vector transmission to accelerate convergence by avoiding local optima.Step size sensitivity is reduced using relaxed Wolfe conditions,which improves computational efficiency without loss of global optimality.Results and Discussions The improved Riemannian gradient optimization algorithm achieves faster convergence and markedly higher WSR performance,attributed to the incorporation of restart strategies and dynamic scaling vector transmission mechanisms,outperforming conventional algorithms(Fig.3).The proposed rank-2 beamforming scheme yields substantially better system performance than traditional rank-1 techniques(Fig.3).Simulations further evaluate the effect of varying the number of IRS reflection elements.Across different configurations,the proposed algorithm consistently enhances WSR and outperforms benchmark algorithms(Fig.4).In addition,it maintains robust performance under varying base station transmit power levels and antenna counts,with rank-2 beamforming preserving clear advantages over rank-1 designs(Fig.5,Fig.6).Finally,simulation results identify optimal IRS deployment positions.System performance peaks when the IRS is placed near the base station or users,whereas intermediate placement leads to performance degradation,highlighting the critical role of deployment strategy in practical applications(Fig.7).Conclusions This study addresses the problem of spectral efficiency maximization in IRS-aided communication systems by proposing a joint rank-2 beamforming and alternating optimization framework.For transmit-side optimization,the WMMSE algorithm is applied to enable efficient power allocation in the rank-2 beamforming design.In parallel,an improved RGA is developed for optimizing the IRS phase shift matrix.This algorithm incorporates adaptive initial step selection based on relaxed Wolfe conditions and integrates restart strategies to avoid local optima.Simulation results confirm that the proposed framework achieves faster convergence and higher user sum rate performance compared to conventional algorithms.Moreover,rank-2 beamforming consistently provides superior system efficiency relative to traditional rank-1 methods across a range of scenarios.
作者
周凯
喻兰
国强
ZHOU Kai;YU Lan;GUO Qiang(Harbin Engineering University,Harbin 150000,China)
出处
《电子与信息学报》
北大核心
2025年第7期2098-2107,共10页
Journal of Electronics & Information Technology
基金
国家重点研发计划(2023YFC2809400)。
关键词
智能反射面
波束成形
频谱效率
黎曼共轭梯度
Intelligent Reflecting Surface(IRS)
Beamforming
Spectral efficiency
Riemannian Gradient Algorithm(RGA)
作者简介
周凯:男,副教授,研究方向为宽带数字通信、无线通信等;通信作者:喻兰,女,硕士生,研究方向为波束成形、智能反射面等,yulan@hrbeu.edu.cn;国强:男,教授,研究方向为5G/6G无线通信关键技术等.
