Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design
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 use...
Published in: | 2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023 |
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Institute of Electrical and Electronics Engineers Inc.
2023
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2-s2.0-85184810358 Alias M.; Subahir S.; Rahman N.H.A. Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design 2023 2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023 10.1109/ISAP57493.2023.10388607 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184810358&doi=10.1109%2fISAP57493.2023.10388607&partnerID=40&md5=4f89d8219e2de3ba4912cd89c893b2d8 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. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Alias M.; Subahir S.; Rahman N.H.A. |
spellingShingle |
Alias M.; Subahir S.; Rahman N.H.A. Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
author_facet |
Alias M.; Subahir S.; Rahman N.H.A. |
author_sort |
Alias M.; Subahir S.; Rahman N.H.A. |
title |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
title_short |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
title_full |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
title_fullStr |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
title_full_unstemmed |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
title_sort |
Binary-Coded Genetic Algorithm Optimization for UHF RFID Tag Antenna Design |
publishDate |
2023 |
container_title |
2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023 |
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container_issue |
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doi_str_mv |
10.1109/ISAP57493.2023.10388607 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184810358&doi=10.1109%2fISAP57493.2023.10388607&partnerID=40&md5=4f89d8219e2de3ba4912cd89c893b2d8 |
description |
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. |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
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language |
English |
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Conference paper |
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scopus |
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Scopus |
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1809677889069645824 |