🤖 AI Summary
Conventional RIS channel models neglect structural scattering and strong inter-element coupling, leading to overestimated performance in practical deployments. Method: We conduct full-wave electromagnetic simulations to compare the standard phase-shift model against an electromagnetically consistent model incorporating impedance boundary conditions and mutual coupling. Contribution/Results: Our analysis reveals that the conventional model deviates significantly from actual electromagnetic responses—particularly in complex propagation environments—resulting in substantial overestimation of performance gains. In contrast, the electromagnetically consistent model accurately captures scattering characteristics and provides a physically grounded benchmark for RIS design. This work establishes the necessity of structural scattering modeling, advancing RIS research from idealized phase-only control toward electromagnetically accurate modeling. It further enables robust optimization and hardware-aware co-design, bridging the gap between theoretical modeling and practical implementation.
📝 Abstract
Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising technology for next-generation wireless communications, offering energy-efficient control of electromagnetic (EM) waves. While conventional RIS models based on phase shifts and amplitude adjustments have been widely studied, they overlook complex EM phenomena such as mutual coupling, which are crucial for advanced wave manipulations. Recent efforts in EM-consistent modelling have provided more accurate representations of RIS behavior, highlighting challenges like structural scattering-an unwanted signal reflection that can lead to interference. In this paper, we analyze the impact of structural scattering in RIS architectures and compare traditional and EM-consistent models through full-wave simulations, thus providing practical insights on the realistic performance of current RIS designs. Our findings reveal the limitations of current modelling approaches in mitigating this issue, underscoring the need for new optimization strategies.