Reducing Simulation Effort for RIS Optimization using an Efficient Far-Field Approximation
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913671470383104 |
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| author | Lang, Hans-Dieter Nyffenegger, Michel A. Mathis, Heinz Zhang, Xingqi |
| author_facet | Lang, Hans-Dieter Nyffenegger, Michel A. Mathis, Heinz Zhang, Xingqi |
| contents | Optimization of Reconfigurable Intelligent Surfaces (RIS) via a previously introduced method is effective, but time-consuming, because multiport impedance or scatter matrices are required for each transmitter and receiver position, which generally must be obtained through full-wave simulation. Herein, a simple and efficient far-field approximation is introduced, to extrapolate scatter matrices for arbitrary receiver and transmitter positions from only a single simulation while still maintaining high accuracy suitable for optimization purposes. This is demonstrated through comparisons of the optimized capacitance values and further supported by empirical measurements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_18583 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reducing Simulation Effort for RIS Optimization using an Efficient Far-Field Approximation Lang, Hans-Dieter Nyffenegger, Michel A. Mathis, Heinz Zhang, Xingqi Optimization and Control Systems and Control Optimization of Reconfigurable Intelligent Surfaces (RIS) via a previously introduced method is effective, but time-consuming, because multiport impedance or scatter matrices are required for each transmitter and receiver position, which generally must be obtained through full-wave simulation. Herein, a simple and efficient far-field approximation is introduced, to extrapolate scatter matrices for arbitrary receiver and transmitter positions from only a single simulation while still maintaining high accuracy suitable for optimization purposes. This is demonstrated through comparisons of the optimized capacitance values and further supported by empirical measurements. |
| title | Reducing Simulation Effort for RIS Optimization using an Efficient Far-Field Approximation |
| topic | Optimization and Control Systems and Control |
| url | https://arxiv.org/abs/2501.18583 |