[Paper Review] System-level Simulation of Reconfigurable Intelligent Surface assisted Wireless Communications System

Qi Gu, Dan Wu+4 more|arXiv (Cornell University)|Jun 29, 2022

Advanced Wireless Communication Technologies4 citations

TL;DR

This paper proposes a system-level simulation framework for Reconfigurable Intelligent Surface (RIS)-assisted wireless networks, modeling realistic RIS element radiation patterns and two-hop signal propagation under line-of-sight (LOS) conditions. Results show that deploying RIS at cell edges with larger RIS arrays (e.g., 40×40 elements) and higher RIS density (16 per sector) yields up to 6.3 dB gain in received signal power and 5.4 dB in SINR, significantly enhancing coverage and spectral efficiency in 6G networks.

ABSTRACT

Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. By smartly reconfiguring the electromagnetic (EM) properties of the metasurface and adjusting the EM parameters of the reflected radio waves, RIS can turn the uncontrollable propagation environment into an artificially reconfigurable space, and thus, can significantly increase the communications capacity and improve the coverage of the system. In this paper, we investigate the far field channel in which the line-of-sight (LOS) propagation is dominant. We propose an antenna model that can characterize the radiation patterns of realistic RIS elements, and consider the signal power received from the two-hop path through RIS. System-level simulations of network performance under various scenarios and parameter.

Motivation & Objective

• To develop a realistic system-level simulation framework for RIS-assisted wireless networks in multi-cell scenarios.
• To model the radiation patterns of real RIS elements using a directional antenna model that accounts for polarization and angular response.
• To evaluate the impact of RIS deployment strategies—such as location, number of elements, and number of RIS panels—on network performance.
• To quantify performance gains in terms of received signal power and SINR under various configurations in a 6G network context.

Proposed method

• Proposes a directional antenna model for RIS elements that captures amplitude patterns in both horizontal and vertical polarization, based on spherical wavefronts and angular response.
• Models path loss using the 3GPP 38.901 Urban Macro (Uma) model for both BS-to-RIS and RIS-to-UE links under LOS conditions.
• Simulates two-hop transmission via RIS, calculating received power and SINR by combining path loss, shadow fading, and beamforming gains from phase-aligned RIS elements.
• Uses a system-level simulator with 7-cell, 21-sector topology, placing RIS at cell edges or center, and varying RIS size (16×16 or 40×40 elements) and count (8 or 16 per sector).
• Analyzes performance under different element spacings (0.5λ, 0.8λ, and 0.4λ) to assess mutual coupling effects.
• Integrates realistic RIS deployment scenarios including single-polarization operation and fixed downtilt angles for BS and RIS.

Experimental results

Research questions

• RQ1 How does RIS deployment at the cell edge compare to deployment in the cell center in terms of received signal power and SINR?
• RQ2 What is the impact of increasing the number of RIS elements per panel (16×16 vs. 40×40) on system performance?
• RQ3 How does increasing the number of RIS panels per sector (8 vs. 16) affect network performance in multi-cell scenarios?
• RQ4 What performance gain is achievable by reducing RIS element spacing (e.g., 0.4λ vs. 0.8λ) in terms of SINR and signal power?
• RQ5 How do path loss and shadow fading models affect the accuracy of RIS-assisted system-level simulations in urban macro environments?

Key findings

• Deploying RIS at the cell edge yields higher performance gains than placing it in the cell center, with up to 6.3 dB improvement in received signal power and 5.4 dB in SINR when using 16 RIS panels of 40×40 elements.
• Increasing the number of RIS elements per panel from 16×16 to 40×40 results in a 1.7 dB increase in received signal power and a 1.9 dB increase in SINR compared to the 16×16 case with 8 panels.
• Doubling the number of RIS panels per sector from 8 to 16 leads to a 1.7 dB gain in received signal power and a 1.9 dB gain in SINR, indicating that RIS density significantly enhances performance.
• Reducing RIS element spacing from 0.8λ×0.5λ to 0.4λ×0.4λ improves SINR performance, demonstrating that tighter element spacing enhances beamforming gain and reduces mutual coupling effects.
• The proposed RIS antenna model effectively captures realistic radiation patterns, enabling accurate system-level simulation of RIS-assisted networks under LOS conditions.
• The simulation results confirm that RIS deployment can significantly improve coverage and spectral efficiency in 6G networks, especially when optimized for element count, panel count, and deployment location.