Qian Yuyan, Deng Honggui, Guo Aimin, Xiao Haoqi, Peng Chengzuo, Zhang Yinhao
School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China.
Sensors (Basel). 2022 Aug 18;22(16):6214. doi: 10.3390/s22166214.
In order to investigate the effect of cooperative Intelligent Reflecting Surface (IRS) in improving spectral efficiency, this paper explores the joint design of active and passive beamforming based on a double IRS-assisted model. First, considering the maximum power constraint of the active vector and the unit modulus constraint of the cooperative passive vector, we establish the non-linear and non-convex optimization problem of multi-user maximization weighted sum rate (WSR). Then, we propose an alternating optimization (AO) algorithm to design the active vector and the cooperative passive vector based on fractional programming (FP) and successive convex approximations (SCA). In addition, we conduct a study on the optimization of the passive reflection vector under discrete phase shift. The simulation results show that the proposed beamforming scheme of double IRS-assisted model performs better than the conventional single IRS-assisted model.
为了研究协作智能反射面（IRS）在提高频谱效率方面的作用，本文基于双IRS辅助模型探索了有源和无源波束成形的联合设计。首先，考虑到有源向量的最大功率约束和协作无源向量的单位模约束，我们建立了多用户最大化加权和速率（WSR）的非线性非凸优化问题。然后，我们提出一种交替优化（AO）算法，基于分数规划（FP）和逐次凸逼近（SCA）来设计有源向量和协作无源向量。此外，我们对离散相移下的无源反射向量优化进行了研究。仿真结果表明，所提出的双IRS辅助模型的波束成形方案比传统的单IRS辅助模型表现更好。
