论文标题
基于歧管优化的多用户速率最大化有助于智能反射表面
Manifold Optimization Based Multi-user Rate Maximization Aided by Intelligent Reflecting Surface
论文作者
论文摘要
在这项工作中，借助智能反射表面（IRS）考虑了与下行链路多用户系统相关的两个问题：加权总和最大化和加权最小速率最大化。对于第一个问题，通过利用矩阵歧管理论并分别使用复杂的球体歧管和复杂的斜形歧管，提出了一种新颖的双流形交替优化（Domalo）算法，并介绍了光束成型的矩阵和反射矢量，从而结合了固有的几何结构和所需的约束。然后，基于dinkelbach型算法和第二个问题的平滑指数惩罚函数，开发出平滑的双流形交替优化（S-Domalo）算法。最后，研究了IRSS和IRS相移之间可能的合作波束形成增益，并研究了有限的分辨率，为实施提供了参考。数值结果表明，我们提出的算法可以显着胜过基准方案。
In this work, two problems associated with a downlink multi-user system are considered with the aid of intelligent reflecting surface (IRS): weighted sum-rate maximization and weighted minimal-rate maximization. For the first problem, a novel DOuble Manifold ALternating Optimization (DOMALO) algorithm is proposed by exploiting the matrix manifold theory and introducing the beamforming matrix and reflection vector using complex sphere manifold and complex oblique manifold, respectively, which incorporate the inherent geometrical structure and the required constraint. A smooth double manifold alternating optimization (S-DOMALO) algorithm is then developed based on the Dinkelbach-type algorithm and smooth exponential penalty function for the second problem. Finally, possible cooperative beamforming gain between IRSs and the IRS phase shift with limited resolution is studied, providing a reference for practical implementation. Numerical results show that our proposed algorithms can significantly outperform the benchmark schemes.
