Optimization of Antenna Isolation Using An Enhanced Multi-Objective Artificial Hummingbird Algorithm Based on Chaotic Sampling

In this paper, a novel enhanced multi-objective artificial hummingbird algorithm is proposed to improve the antenna isolation by optimizing the geometric parameters of each antenna. An effective chaotic sampling method is used to obtain discrete random samples. An antenna array is taken as an exampl...

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Bibliographic Details
Published in:	IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (Online) pp. 1 - 3
Main Authors:	Qin, Peng-Fei, Li, Xiao-Dong, Liu, Hao-Lei, Wang, Dong, Huang, Guan-Long, Chen, Rui-Sen
Format:	Conference Proceeding
Language:	English
Published:	IEEE 27.11.2022
ISSN:	2694-2992
Online Access:	Get full text
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Summary:	In this paper, a novel enhanced multi-objective artificial hummingbird algorithm is proposed to improve the antenna isolation by optimizing the geometric parameters of each antenna. An effective chaotic sampling method is used to obtain discrete random samples. An antenna array is taken as an example to verify the performance of the tuning method. Results show that the proposed approach is able to achieve a better antenna isolation without any additional decoupling structure.
ISSN:	2694-2992
DOI:	10.1109/IMWS-AMP54652.2022.10107129