This paper introduces a high-fidelity electromagnetic simulation tool based on the Partial Element Equivalent Circuit (PEEC) method for the analysis of Reconfigurable Intelligent Surfaces (RIS). The tool supports the simulation of RIS under both plane wave illumination and more complex configurations involving transmitter-RIS-receiver interactions. It also enables the modeling of radiating elements connected to arbitrary external impedances. Implemented in Julia, the proposed framework demonstrates significant improvements in computational efficiency compared to traditional MAT-LAB implementations, particularly in matrix assembly and solution time. In the example presented in this paper, this translates into a reduction of computation time by approximately 84%, highlighting the practical benefits of the Julia-based approach for large-scale problems. The flexibility and precision of the tool make it a valuable asset for the optimized design and analysis of RIS in next-generation wireless communication systems.
A Software Tool for Robust and Reliable Electromagnetic Models: The case of Reconfigurable Intelligent Surfaces
Pettanice G.;Vittoria E.;Frittella G.;Romano D.;Valentini R.;Di Marco P.;D'Emidio M.;Cicerone S.;Santucci F.;Di Renzo M.;Antonini G.
2025-01-01
Abstract
This paper introduces a high-fidelity electromagnetic simulation tool based on the Partial Element Equivalent Circuit (PEEC) method for the analysis of Reconfigurable Intelligent Surfaces (RIS). The tool supports the simulation of RIS under both plane wave illumination and more complex configurations involving transmitter-RIS-receiver interactions. It also enables the modeling of radiating elements connected to arbitrary external impedances. Implemented in Julia, the proposed framework demonstrates significant improvements in computational efficiency compared to traditional MAT-LAB implementations, particularly in matrix assembly and solution time. In the example presented in this paper, this translates into a reduction of computation time by approximately 84%, highlighting the practical benefits of the Julia-based approach for large-scale problems. The flexibility and precision of the tool make it a valuable asset for the optimized design and analysis of RIS in next-generation wireless communication systems.| File | Dimensione | Formato | |
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