Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design

• Published in: 2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023
• Main Author: Alias M.; Subahir S.; Rahman N.H.A.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184810358&doi=10.1109%2fISAP57493.2023.10388607&partnerID=40&md5=4f89d8219e2de3ba4912cd89c893b2d8
• DOI: 10.1109/ISAP57493.2023.10388607

This paper proposes a fragmented Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tag antenna design. A fragmented design is portrayed to enhance the conjugate matching between chip impedance and antenna impedance utilizing the Binary Genetic Algorithm (BGA) method. The substrate used is Rogers 5880 with a thickness of 1.57mm and a relative permittivity of 2.2. The chip used is NXP Ucode 8 with a chip impedance of 13-j191 Ω. The framework is implemented in MATLAB and verified by CST simulation software. In the proposed design, the resonant frequency is at 909MHz without a chip footprint, whereas with the inclusion of a chip footprint, the resonant frequency shifts to 917MHz. Profound results are obtained utilizing the BGA method with the chip footprint where the reflection coefficient (S11) is - 21.11dB, maximum power transfer of 0.99, and antenna impedance of 11.08+j191.91 Ω. © 2023 IEEE.