On the Limitations of Ray-Tracing for Learning-Based RF Tasks in Urban Environments

TL;DR

This study evaluates the accuracy of ray-tracing simulations for outdoor cellular links in urban Rome, revealing that antenna placement and orientation significantly impact fidelity, and highlighting the challenge of modeling urban noise for high-fidelity RF simulations.

Contribution

It systematically assesses ray-tracing simulation fidelity in urban environments and demonstrates that antenna configurations are crucial for accurate RF modeling, with implications for learning-based RF tasks.

Findings

Antenna location and orientation are critical for simulation accuracy.

Optimizing antenna placement improves correlation and localization accuracy.

Urban noise modeling remains a key challenge for high-fidelity RF simulation.

Abstract

We study the realism of Sionna v1.0.2 ray-tracing for outdoor cellular links in central Rome. We use a real measurement set of 1,664 user-equipments (UEs) and six nominal base-station (BS) sites. Using these fixed positions we systematically vary the main simulation parameters, including path depth, diffuse/specular/refraction flags, carrier frequency, as well as antenna's properties like its altitude, radiation pattern, and orientation. Simulator fidelity is scored for each base station via Spearman correlation between measured and simulated powers, and by a fingerprint-based k-nearest-neighbor localization algorithm using RSSI-based fingerprints. Across all experiments, solver hyper-parameters are having immaterial effect on the chosen metrics. On the contrary, antenna locations and orientations prove decisive. By simple greedy optimization we improve the Spearman correlation by 5% to 130% for various base stations, while kNN-based localization error using only simulated data as reference points is decreased by one-third on real-world samples, while staying twice higher than the error with purely real data. Precise geometry and credible antenna models are therefore necessary but not sufficient; faithfully capturing the residual urban noise remains an open challenge for transferable, high-fidelity outdoor RF simulation.