RIS Optimization Algorithms for Urban Wireless Scenarios in Sionna RT

TL;DR

This paper assesses RIS optimization algorithms in urban environments using Sionna RT simulations, comparing various strategies and emphasizing the importance of realistic testing for reliable performance evaluation.

Contribution

It implements and benchmarks RIS optimization algorithms based on channel estimation within Sionna RT simulations for urban scenarios.

Findings

RIS algorithms' performance varies with deployment conditions.

Simulation results highlight the importance of realistic environment validation.

Coverage maps demonstrate RIS effectiveness in urban settings.

Abstract

This paper evaluates the performance of reconfigurable intelligent surface (RIS) optimization algorithms, which utilize channel estimation methods, in ray tracing (RT) simulations within urban digital twin environments. Beyond Sionna's native capabilities, we implement and benchmark additional RIS optimization algorithms based on channel estimation, enabling an evaluation of RIS strategies under various deployment conditions. Coverage maps for RIS-assisted communication systems are generated through the integration of Sionna's RT simulations. Moreover, real-world experimentation underscores the necessity of validating algorithms in near-realistic simulation environments, as minor variations in measurement setups can significantly affect performance.