Non-Uniform Metamaterial Mushroom Antennas via a Genuine Multi-Objective Bayesian Optimization Method

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Non-Uniform Metamaterial Mushroom Antennas via a Genuine Multi-Objective Bayesian Optimization Method
Title:
Non-Uniform Metamaterial Mushroom Antennas via a Genuine Multi-Objective Bayesian Optimization Method
Journal Title:
2024 18th European Conference on Antennas and Propagation (EuCAP)
Keywords:
Publication Date:
26 April 2024
Citation:
Zeng, Y., Qing, X., & Chia, M. Y.-W. (2024, March 17). Non-Uniform Metamaterial Mushroom Antennas via a Genuine Multi-Objective Bayesian Optimization Method. 2024 18th European Conference on Antennas and Propagation (EuCAP). https://doi.org/10.23919/eucap60739.2024.10501115
Abstract:
Three broadband non-uniform metamaterial mushroom antennas are designed with distinct mushroom configurations. The design trade-offs among the input impedance bandwidth, boresight gain, and the front-to-back ratio are considered with a genuine multi-objective Bayesian optimization method. The three non-uniform antennas attain a notable increase in impedance bandwidth with different degrees of trade-off in terms of the other two design targets when compared to the reference antenna with uniform mushroom configuration. All the four antennas are prototyped and measured, with strong alignment between simulation and measurement. The optimized designs can function in the n77 band of 5G New Radio.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - AME YIRG Fund
Grant Reference no. : A2084c0173
Description:
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-88-31299-09-1
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