Reconfigurable intelligent surfaces (RISs) are envisioned to play a key role in future wireless communication networks. However, channel estimation in RIS-aided wireless networks is challenging due to their passive nature and the large number of reflective elements, leading to high channel estimation overhead. Additionally, conventional methods like beam sweeping, which do not rely on explicit channel state information, often struggle in managing interference in multi-user networks. In this paper, we propose a novel approach that leverages digital twins (DTs) of the physical environments to approximate channels using electromagnetic 3D models and ray tracing, thus relaxing the need for channel estimation and extensive over-the-air computations in RIS-aided wireless networks. To address the digital twins channel approximation errors, we further refine this approach with a DT-specific robust transmission design that reliably meets minimum desired rates. The results show that our method secures these rates over 90% of the time, significantly outperforming beam sweeping, which achieves these rates less than 8% of the time due to its poor management of transmitting power and interference.

翻译：可重构智能表面（RIS）被寄望在未来无线通信网络中发挥关键作用。然而，由于RIS的无源特性及其大量反射单元，RIS辅助无线网络中的信道估计面临巨大挑战，导致高昂的信道估计开销。此外，不依赖显式信道状态信息的传统方法（如波束扫描）在多用户网络中往往难以有效管理干扰。本文提出一种创新方法，利用物理环境的数字孪生（DT）技术，通过电磁三维模型与射线追踪来近似信道，从而降低RIS辅助无线网络中对信道估计和大量空口计算的需求。为应对数字孪生信道近似误差，我们进一步提出针对DT的鲁棒传输设计方案，确保系统可靠满足最低期望速率。实验结果表明，该方法在超过90%的时间内能保障目标速率，显著优于波束扫描方案——因其在发射功率与干扰管理方面的不足，后者实现目标速率的概率不足8%。