@inproceedings{3b5586dc1d9243a7a71b47e9ee91f659,
title = "A Physics-Informed Bayesian Approach for RIS Optimization in Complex Wireless Channels",
abstract = "We introduce a Bayesian optimization framework for sum rate maximization in RIS-assisted MU-MIMO systems. The decision variables include discrete RIS phase shifts and continuous array precoding vectors. This yields a non-convex, combinatorial problem that challenges conventional optimization methods. This paper proposes a Bayesian surrogate model with physics-informed bases and geometric embeddings to navigate the large configuration space. The work greatly reduces computational complexity and pilot overhead while delivering fast convergence towards near-optimal performance.",
author = "Charles Ross and Zhen Peng",
note = "Publisher Copyright: {\textcopyright} 2025 ACES.; 2025 International Applied Computational Electromagnetics Society Symposium, ACES-Orlando 2025 ; Conference date: 18-05-2025 Through 21-05-2025",
year = "2025",
doi = "10.23919/ACES66556.2025.11052465",
language = "English (US)",
series = "2025 International Applied Computational Electromagnetics Society Symposium, ACES-Orlando 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2025 International Applied Computational Electromagnetics Society Symposium, ACES-Orlando 2025",
address = "United States",
}