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System-Level Experimental Evaluation of Reconfigurable Intelligent Surfaces for NextG Communication Systems

Maria Tsampazi, Tommaso Melodia

TL;DR

This work tackles the lack of end-to-end evaluation for RIS-enabled NextG networks by combining Geometry-Based Stochastic Channel Modeling with QuaDRiGa, a hierarchical Stackelberg game for energy-efficient power control, and full-stack Colosseum emulation using srsRAN. It demonstrates frequency-dependent RIS gains across Sub-6 GHz and mmWave bands, via a RIS-UAV system with |M| elements and cascaded channel gains $G_i=|h_{iU}+oldsymbol{h}_{RU}^Holdsymbol{oldsymbol{ heta}} oldsymbol{h}_{iR}|^2$, and shows substantial energy savings at mmWave and latency improvements for URLLC in Sub-6 GHz with modest RIS deployment. The study validates the approach through QuaDRiGa simulations and Colosseum-based experiments, highlighting that RIS-enabled systems can achieve notable performance gains across network slices while balancing power and interference. Overall, the work provides a practical, cross-layer framework for evaluating RIS in NextG networks and informs deployment guidance for RIS scale (e.g., ~100 elements for Sub-6 GHz, ~1000 for mmWave) to meet energy efficiency and latency objectives.

Abstract

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.

System-Level Experimental Evaluation of Reconfigurable Intelligent Surfaces for NextG Communication Systems

TL;DR

This work tackles the lack of end-to-end evaluation for RIS-enabled NextG networks by combining Geometry-Based Stochastic Channel Modeling with QuaDRiGa, a hierarchical Stackelberg game for energy-efficient power control, and full-stack Colosseum emulation using srsRAN. It demonstrates frequency-dependent RIS gains across Sub-6 GHz and mmWave bands, via a RIS-UAV system with |M| elements and cascaded channel gains , and shows substantial energy savings at mmWave and latency improvements for URLLC in Sub-6 GHz with modest RIS deployment. The study validates the approach through QuaDRiGa simulations and Colosseum-based experiments, highlighting that RIS-enabled systems can achieve notable performance gains across network slices while balancing power and interference. Overall, the work provides a practical, cross-layer framework for evaluating RIS in NextG networks and informs deployment guidance for RIS scale (e.g., ~100 elements for Sub-6 GHz, ~1000 for mmWave) to meet energy efficiency and latency objectives.

Abstract

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.

Paper Structure

This paper contains 12 sections, 1 theorem, 11 equations, 10 figures, 6 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Work
  3. with QuaDRiGa
  4. Channel Modeling with QuaDRiGa
  5. Experimentation through Simulation with QuaDRiGa
  6. for Wireless Network Channel Emulators
  7. Investigating Energy Efficiency with frequency-dependent and in
  8. System Model: A -assisted setup with QuaDRiGa
  9. Hierarchical Game-Theoretic Power Control
  10. Comparison with the state-of-the-art
  11. Performance Evaluation of RIS-Assisted Communication Systems on Colosseum
  12. Conclusion

Key Result

Theorem 1

(Existence & Uniqueness of a Nash Equilibrium) For the non-cooperative game given as $G=[I,\{A_i\}_{\forall i \in I}, \{U_i\}_{\forall i \in I}]$, there exists a unique Nash equilibrium point, which is defined as follows: where $\gamma_{i}^{*}$ represents the unique positive solution to the equation $\frac{\partial f(\gamma_i)}{\partial \gamma_{i}} \gamma_{i}-f(\gamma_{i})=0, f(\gamma_{i})=(1-e^{-

Figures (10)

  • Figure 1: Results averaged over 100 channel realizations for the link describing green vehicle's transmission to the red in Willow Grove Naval Air Base in Horsham Township, Pennsylvania, USA.
  • Figure 2: cellular metrics between -node 1 and -node 2.
  • Figure 3: -assisted and -enabled communications system.
  • Figure 4: A Hierarchical Stackelberg Game-Theoretic Approach to Energy-Efficient Power Control.
  • Figure 5: Evaluation of the hierarchical game-theoretic power control framework per , under different number of elements and different bands.
  • ...and 5 more figures

Theorems & Definitions (2)

  • Definition 1
  • Theorem 1