Space–Time Adaptive Modeling and Shape Optimization of Microwave Structures With Applications to Metasurface Design

Zhao, Qiming; Sarris, Costas D.

doi:10.1109/tmtt.2022.3197806

Cited by 9 publications

(6 citation statements)

References 38 publications

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“…For example, [4], [5] adopted the gain model of cos α θ (α is a parameter to be tuned and θ is the elevation angle) inspired by patch antennas to calculate E sc,i . In addition to disregarding mutual coupling, [4]- [6] did not consider distinct features of specific RISs, e.g., their geometries, which strongly affect the RIS behavior [17], [18]. As a result, these methods had limited accuracy in the computation of main and side lobes.…”

Section: A Computing Ris Scattered Fields Based On the Array Theorymentioning

confidence: 99%

A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces

Liu,

Sarris

2024

Preprint

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The cell-to-cell coupling in a reconfigurable intelligent surface (RIS) is very different from a periodic structure, where coupling effects can be precisely evaluated via full-wave analysis with periodic boundary conditions. We propose a novel method based on convolutional neural networks (CNNs), to predict the contribution of mutual coupling on the near-zone tangential electric field of every RIS unit cell that characterizes its scattering. Our CNN model incorporates an attention mechanism based on the squeeze-and-excitation block module, enhancing its capability to discern and quantify coupling effects, especially from neighboring cells surrounding the unit cell of interest. The predictions of the model enable the computation of RIS scattered fields, fully accounting for the aperiodic nature of an RIS. Comparisons to finite-element analysis confirm that our computed fields are accurate at any point and for any RIS configuration. Furthermore, our trained model can be re-trained through transfer learning, to accurately and efficiently predict cell-to-cell coupling under different incident wave conditions, utilizing only a reduced number of training data. Therefore, the proposed method is a valuable tool for various practical applications, such as synthesizing RIS scattered field patterns and evaluating the performance of RIS-enabled channels.

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Section: A Computing Ris Scattered Fields Based On the Array Theorymentioning

confidence: 99%

A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces

Liu,

Sarris

2024

Preprint

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“…In the increasingly complex EM world, digital coding and programmable metamaterials and metasurfaces have been enabling commercial opportunities with broad impact on wireless communications, in particular, reconfigurable intelligent surfaces (RIS), based on metamaterials and metasurfaces, have potential advantages in advanced wireless communication (6G). In order to create a forum for researchers and engineers, a Focus Topic on metamaterials and metasurfaces has been created in issues of March and April 2021 as well as January and December 2022 with 19 papers in total [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], those papers have been grouped from regular papers on the topic. Then, a Special Issue on Metamaterials, Metadevices, and Applications has been approved, the submission deadline to this special issue is December 20, 2022, expected to be published in July 2023.…”

Section: More Details Have Been Shown Inmentioning

confidence: 99%

Editorial From Theories to Techniques and Technologies in the Frequency Range of MHz to THz

2022

IEEE Trans. Microwave Theory Techn.

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“…However, the geometry of unit cells can be very different from that of a rectangular patch. In fact, extensive research efforts are dedicated to tailoring unit cell geometries of metasurfaces, to achieve various performance objectives [13]- [15]. Moreover, this model ignored the substrate and the conducting ground plane that play important roles in the response of a unit cell to an incident plane wave.…”

Section: Introductionmentioning

confidence: 99%

Efficient Computation of Scattered Fields From Reconfigurable Intelligent Surfaces for Propagation Modeling

Liu,

Sarris

2024

IEEE Trans. Antennas Propagat.

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We propose a method to efficiently compute the scattered electric field of a reconfigurable intelligent surface (RIS) for multiple configurations. In contrast to most existing methods that assume that each unit cell scatters an incident wave individually instead of collectively, our method accounts for the mutual coupling of unit cells. This allows us to estimate the scattered fields in the main scattering direction of an RIS, at an accuracy that is comparable to full-wave analysis. Furthermore, combined with ray-tracing, the computed scattered fields can be used to model wave propagation in realistic, multipath radio environments with RISs. Hence, our method efficiently addresses three critical considerations for the analysis of RIS-enabled links: mutual coupling between unit cells of an RIS, mutlipath effects in the channel due to the RIS acting as a diffuse scatterer, and the variability of the RIS scattering properties that requires extensive computational effort to account for.

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Space–Time Adaptive Modeling and Shape Optimization of Microwave Structures With Applications to Metasurface Design

Cited by 9 publications

References 38 publications

A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces

A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces

Editorial From Theories to Techniques and Technologies in the Frequency Range of MHz to THz

Efficient Computation of Scattered Fields From Reconfigurable Intelligent Surfaces for Propagation Modeling

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