Intelligent reflecting surfaces (IRSs) are an emerging technology for future wireless communication. The vast majority of recent research on IRS has focused on system level optimizations. However, developing straightforward and tractable electromagnetic (EM) models that are suitable for IRS aided communication modeling remains an open issue. In this paper, we address this issue and derive communication models by using rigorous scattering parameter network analysis. We also propose new IRS architectures based on group and fully connected reconfigurable impedance networks, which are more general and more efficient than conventional single connected reconfigurable impedance network. In addition, the scaling law of the received signal power of an IRS aided system with reconfigurable impedance networks is also derived. Compared with the single connected reconfigurable impedance network, our group and fully connected reconfigurable impedance network can increase the received signal power by up to 62%, or maintain the same received signal power with a number of IRS elements reduced by up to 21%. We also investigate the proposed architecture in deployments with distance-dependent pathloss and Rician fading channel, and show that the proposed group and fully connected reconfigurable impedance networks outperform the single connected case by up to 34% and 48%, respectively.

中文翻译：

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基于散射参数网络分析的智能反射面建模与架构设计

智能反射面（IRS）是用于未来无线通信的新兴技术。关于IRS的最新研究绝大多数集中在系统级优化上。但是，开发适用于IRS辅助通信建模的简单易懂的电磁（EM）模型仍然是一个悬而未决的问题。在本文中，我们解决了这个问题，并使用严格的散射参数网络分析得出了通信模型。我们还提出了基于组和完全连接的可重配置阻抗网络的新IRS体系结构，它比常规的单连接可重配置阻抗网络更通用，更高效。此外，还推导了具有可重配置阻抗网络的IRS辅助系统的接收信号功率的缩放定律。与单连接可重配置阻抗网络相比，我们的组和全连接可重配置阻抗网络可以将接收信号功率提高多达62％，或者在多个IRS元件减少多达21％的情况下保持相同的接收信号功率。我们还研究了在与距离相关的路径损耗和Rician衰落信道的部署中所提出的体系结构，并表明所提出的组和完全连接的可重配置阻抗网络的性能分别比单个连接情况高34％和48％。