journal article·2025-11-11Open access

Multi-Polar Approach to Parasitic Suppression in Smart Electromagnetic Skins (SESs)

Shahid Ayaz, Paola Pirinoli

Applied Sciences· Volume 15· Issue 22

Abstract

Smart Electromagnetic Skins (SESs) provide a cost-effective and efficient alternative to increasing the number of Base Stations (BSs) for improving the performance of next-generation communication networks and contribute to the implementation of Smart Radio Environments (SREs). SESs generalize the concept of ReflectArrays (RAs) because they redirect the incident field in a non-specular direction. However, as the difference between the pointing and specular directions increases, specular and parasitic effects arise, which affect the radiation pattern, energy efficiency, and pointing direction. The techniques generally adopted for SES design, using homogenized-effective-medium model, are unable to overcome this drawback efficiently. Starting with initial SES design based on the Phase-Gradient (PG) approach, the suppression of the higher order modes has been achieved by incorporating volumetric charge-current distributions when defining radiation modes, using theory of electromagnetic-multipoles. This approach reveals formation of anapoles in single-layer SESs/RAs for first time ever. By combining both local and non-local approaches in super-cell design, higher-order symmetry-breaking of unit cells is utilized to exploit anapole formation as a parasitic mode suppression method. Numerical analysis of SESs with increasing size confirms the effectiveness of the proposed approach, which allows for a drastic reduction in parasitic modes while leaving the performance of the desired mode unchanged. Adopting a multipole perspective enhances the understanding of SES radiation mechanisms, unlocks their unexploited performance potential, and opens new opportunities for multifunctional design.
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Research context

OpenAlex topics: Advanced Antenna and Metasurface Technologies · Antenna Design and Analysis · Energy Harvesting in Wireless Networks

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electronics and Telecommunications (DET), Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Turin, Italy

Funding

European Union

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