Site-Specific RIS Deployment in Cellular Networks via Calibrated Ray Tracing

TL;DR

This paper tackles the challenge of site-specific RIS deployment in urban cellular networks by leveraging a calibrated ray-tracing digital twin to jointly optimize RIS placement, orientation, phase configuration, and BS beamforming across 4G/5G/6G bands. It introduces a physics-consistent RIS model and a data-driven deployment workflow that uses outage UE clustering and ray-based heuristics to scale RIS deployments in a real-world urban layout validated with measured data. Material property calibration against measurements improves ray-tracing accuracy, enabling realistic evaluations of coverage gains; results show that substantial improvements demand dense, large-aperture RIS deployments, which raises questions about economic viability. The framework is implemented in open-source form, enabling reproducibility and exploration of multi-band RIS strategies in city-scale digital twins.

Abstract

This work introduces a fully-automated RIS deployment strategy validated through a digital twin, powered by Sionna ray tracing, of a UK city. On a scene calibrated with measured data, the method jointly optimizes RIS placement, orientation, configuration, and BS beamforming across 4G, 5G, and hypothetical 6G frequencies. Candidate RIS sites are identified via scattering-based rays, while user clustering reduces deployment overhead. Results show that meaningful coverage enhancement requires dense, large-aperture RIS deployments, raising questions about the practicality and cost of large-scale RIS adoption.

Figures (7)

• Figure 1: 3D visualization of the area produced with OpenStreetMap, with black pins indicating BS sites.
• Figure 2: Distribution of RSRP prediction errors.
• Figure 3: RSRP heatmaps across the considered urban area for 4G, 5G, and 6G.
• Figure 4: Number of clusters formed by the BIRCH algorithm vs. parameter $T$ across the considered frequency bands.
• Figure 5: RSRP enhancement from deploying the maximum number of RIS.