EPJ Appl. Metamat.
Volume 4, 2017
Metamaterials'2017 – Metamaterials and Novel Wave Phenomena: Theory, Design and Application
|Number of page(s)||6|
|Published online||31 October 2017|
High data density and capacity in chipless radiofrequency identification (chipless-RFID) tags based on double-chains of S-shaped split ring resonators (S-SRRs)
CIMITEC, Departament d'Enginyeria Electrònica, Universitat Autònoma de Barcelona,
* e-mail: Ferran.Martin@uab.cat
Received in final form: 7 October 2017
Accepted: 10 October 2017
Published online: 1 November 2017
The data density per surface (DPS) is a figure of merit in chipless radiofrequency identification (chipless-RFID) tags. In this paper, it is demonstrated that chipless-RFID tags with high DPS can be implemented by using double-chains of S-shaped split ring resonators (S-SRRs). Tag reading is achieved by near-field coupling between the tag and the reader, a CPW transmission line fed by a harmonic signal tuned to the resonance frequency of the S-SRRs. By transversally displacing the tag over the CPW, the transmission coefficient of the line is modulated by tag motion. This effectively modulates the amplitude of the injected (carrier) signal at the output port of the line, and the identification (ID) code, determined by the presence or absence of S-SRRs at predefined and equidistant positions in the chains, is contained in the envelope function. The DPS is determined by S-SRR dimensions and by the distance between S-SRRs in the chains. However, by using two chains of S-SRRs, the number of bits per unit length that can be accommodated is very high. This chipless-RFID system is of special interest in applications where the reading distance can be sacrificed in favor of data capacity (e.g., security and authentication). Encoding of corporate documents, ballots, exams, etc., by directly printing the proposed tags on the item product to prevent counterfeiting is envisaged.
Key words: chipless RFID / coplanar waveguide / split ring resonators / high data capacity / security applications
© C. Herrojo et al., published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.