Reconfigurable Intelligent Surfaces (RISs) are a promising technique for enhancing the performance of Next Generation (NextG) wireless communication systems in terms of both spectral and energy efficiency, as well as resource utilization. However, current RIS research has primarily focused on theoretical modeling and Physical (PHY) layer considerations only. Full protocol stack emulation and accurate modeling of the propagation characteristics of the wireless channel are necessary for studying the benefits introduced by RIS technology across various spectrum bands and use-cases. In this paper, we propose, for the first time: (i) accurate PHY layer RIS-enabled channel modeling through Geometry-Based Stochastic Models (GBSMs), leveraging the QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) open-source statistical ray-tracer; (ii) optimized resource allocation with RISs by comprehensively studying energy efficiency and power control on different portions of the spectrum through a single-leader multiple-followers Stackelberg game theoretical approach; (iii) full-stack emulation and performance evaluation of RIS-assisted channels with SCOPE/srsRAN for Enhanced Mobile Broadband (eMBB) and Ultra Reliable and Low Latency Communications (URLLC) applications in the worlds largest emulator of wireless systems with hardware-in-the-loop, namely Colosseum. Our findings indicate (i) the significant power savings in terms of energy efficiency achieved with RIS-assisted topologies, especially in the millimeter wave (mmWave) band; and (ii) the benefits introduced for Sub-6 GHz band User Equipments (UEs), where the deployment of a relatively small RIS (e.g., in the order of 100 RIS elements) can result in decreased levels of latency for URLLC services in resource-constrained environments.

翻译：可重构智能表面（RIS）是一种提升下一代（NextG）无线通信系统性能的前沿技术，可在频谱效率、能量效率及资源利用率方面带来显著增益。然而，当前RIS研究主要集中于理论建模与物理（PHY）层分析。为探究RIS技术在不同频段与应用场景中的优势，需进行全协议栈仿真并建立无线信道传播特性的精确模型。本文首次提出：（i）基于几何随机模型（GBSMs），利用开源统计射线追踪器QUAsi Deterministic RadIo channel GenerAtor（QuaDRiGa）实现精确的PHY层RIS信道建模；（ii）通过单领导者多跟随者Stackelberg博弈理论方法，全面研究不同频谱段的能量效率与功率控制，实现RIS辅助的优化资源分配；（iii）在目前全球最大的硬件在环无线系统仿真平台Colosseum上，利用SCOPE/srsRAN对增强移动宽带（eMBB）与超高可靠低时延通信（URLLC）应用进行RIS辅助信道的全栈仿真与性能评估。研究结果表明：（i）RIS辅助拓扑结构可显著提升能量效率并实现功率节约，在毫米波（mmWave）频段尤为突出；（ii）在Sub-6 GHz频段用户设备（UE）中，部署规模较小的RIS（例如约100个RIS单元）可在资源受限环境下有效降低URLLC服务的时延水平。