An innovative method has developed recently for biasing the varactors of a reconfigurable intelligent surface (RIS) by utilizing resonant standing waves on the “biasing transmission line (TL)” [E. Ayanoglu, F. Capolino, and A. L. Swindlehurst, “Wave-controlled metasurface-based reconfigurable intelligent surfaces,” IEEE Wireless Communications, vol. 29, no. 4, pp. 86-92,2022] located beneath the reflective surface. Using this approach, each RIS element does not require separate external biasing. For estimating the RIS reflection properties controlled by varactors, we analyze a planar array with phase gradient in one direction, of side length L, of reconfigurable elements. We employ the analytical model for predicting the reflection coefficients of the unit cells presented in [D. Hanna, M. Saavedra-Melo, F. Shan, and F. Capolino, “A versatile polynomial model for reflection by a reflective intelligent surface with varactors,” IEEE AP-S/URSI, 2022] and investigate how the standing wave biasing approach compares with the traditional way to generate field patterns of the reflected wave.
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Wave-Controlled RIS: A Novel Method for Reconfigurable Elements Biasing
A novel method for biasing the varactors of a reconfigurable intelligent surface (RIS) by using resonant standing waves on the biasing transmission line (TL) at a layer below the RF reflective surface to eliminate the need to bring external bias for each element of the RIS is described. We use an analytical model of the RIS to compare the field pattern of the reflected wave by (i) considering the ideal case, (ii) the case where reflection accounts for the varactor's model, and (iii) the case as in (ii) but where the biasing voltage distribution is constructed by using the wave control (i.e., standing waves).
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- Award ID(s):
- 2030029
- PAR ID:
- 10543696
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 978-1-6654-4228-2
- Page Range / eLocation ID:
- 979 to 980
- Format(s):
- Medium: X
- Location:
- Portland, OR, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/USNC-URSI52151.2023.10237459
