20.500.12556/DiRROS-29348 SABER symbolic regression-based angle of arrival and beam pattern estimator SABER: symbolic regression-based angle of arrival and beam pattern estimator Accurate angle-of-arrival (AoA) estimation is essential for next-generation wireless communication systems to enable reliable beamforming, high-precision localization, and integrated sensing. Unfortunately, classical high-resolution techniques require multielement arrays and extensive snapshot collection, while generic machine-learning (ML) approaches often yield black-box models that lack physical interpretability. To address these limitations, we propose a symbolic regression (SR)-based ML framework. Namely, symbolic regression-based angle of arrival and beam pattern estimator (SABER), a constrained SR framework that automatically discovers closed-form beam pattern and AoA models from path loss measurements with interpretability. SABER achieves high accuracy while bridging the gap between opaque ML methods and interpretable physics-driven estimators. First, we validate our approach in a controlled free-space anechoic chamber, showing that both direct inversion of the known cos[sup]n beam and a low-order polynomial surrogate achieve sub-0.5° mean absolute error (MAE). A purely unconstrained SR method can further reduce the error of the predicted angles, but produces complex formulas that lack physical insight. Then, we implement the same SR-learned inversions in a real-world, reconfigurable intelligent surface (RIS)-aided indoor testbed. SABER and unconstrained SR models accurately recover the true AoA with near-zero error. Finally, we benchmark SABER against the Cramér–Rao lower bounds (CRLBs). Our results demonstrate that SABER is an interpretable and accurate alternative to state-of-the-art and black-box ML-based methods for AoA estimation. angle of arrival estimation reconfigurable intelligent surface symbolic regression kot prihoda ocena true false true IEEE ZDA Angleški jezik Slovenski jezik © 2026 The Authors. Neznano 2026-05-11 13:14:35 2026-05-11 13:14:35 2026-05-12 03:46:58 0000-00-00 00:00:00 2026 0 0 Nasl. z nasl. zaslona; Soavtorja iz Slovenije: Carolina Fortuna, Jernej Hribar; Opis vira z dne 8. 5. 2026; str. [1-13] Vol. 75, article no. 5501213 27 Apr. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-10-30 2026-04-07 2026-05-07 004.8 1557-9662 10.1109/TIM.2026.3687328 277527043 https://ieeexplore.ieee.org/document/11494930 1 a0e83fdd-4d2a-11f1-8a5a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=43959 RAZ_Chou_Shih-Kai_2026.pdf RAZ_Chou_Shih-Kai_2026.pdf 1 EDB3C987686F9981759FBEBF94113985 ca52aaea7e5e9acd4000b23e67601ae77e3442afa6fa2c8cd7442ad379ceed2b 6b67cf50-4d2b-11f1-8a5a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=43960 Institut Jožef Stefan 0 0 0