Smart Radio Environment via a Network of Distributed Tags Acting as a Reconfigurable Intelligent Surface
This paper aims to demonstrate that a network of tags can be econtrolledf (or configured) to improve communication between two radio nodes, using the same principle as for reconfigurable intelligent surfaces (RIS). RIS enables dynamic, targeted control of radio signals between a transmitter and a receiver, considering the propagation environment to optimize the radio link. However, RIS have to be specially deployed, and face the problem of remote control and energy supply. Assuming that future generations of passive RFID tags will incorporate the ability to switch between different load impedances in a reader-controlled way, the concept proposed here is to use tag networks already present in the environment as RIS. In addition to demonstrating this concept through several scenarios, the aim here is to introduce and compare different strategies for optimizing the choice of load impedances. The proposed analysis is also based on two modeling approaches: the first, based on the Friis equation, provides a clear illustration of the concept and its issues; the second, more general and realistic, is based on an..-port electrical equivalent model, and enables us to consider tag networks with more complex geometries, with no constraints on inter-tag distances. The results obtained are promising and demonstrate the potential of such an approach.
Authors
- Daniel Sánchez (ORCID: https://orcid.org/0000-0002-2453-2904)
- Ognadon Assogba (ORCID: https://orcid.org/0000-0002-7643-9277)
- Yvan Duroc (ORCID: https://orcid.org/0000-0003-0079-5969)
- Guillaume Villemaud (ORCID: https://orcid.org/0000-0002-7550-3863)
- Lilian Michalak
Institutions
- Université Claude Bernard Lyon 1 (FR)
- Centre National de la Recherche Scientifique (FR)
- Laboratoire Ampère (FR)
- Institut National des Sciences Appliquées de Lyon (FR)
Publication Details
- Journal
- IEEE Journal of Radio Frequency Identification
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jrfid.2025.3596397
- Primary Topic
- DNA and Biological Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00