Journal
APPLIED SCIENCES-BASEL
Volume 10, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/app10010378
Keywords
cross-dipole antenna; artificial neural network; isolation improvement; wireless communication
Categories
Funding
- National Key Research and Development Program of China [2017YFA0204600]
- National Natural Science Foundation of China [51802352]
- Fundamental Research Funds for the Central Universities of Central South University [2018zzts355]
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In this manuscript, a resonator layer is presented for the purpose of reducing the mutual coupling effect between each antenna element of a cross dipole antenna. In design processes, an artificial neural network approach was used for various resonator designs. In the operating frequency band of 2.2-2.7 GHz, 48 different 6 x 6 resonator layers were created and integrated into the cross dipole antenna to reduce transmission and improve isolation between each antenna elements. Moreover, when training an artificial neural network in the Matlab program, 48 different resonator layers were used with the return losses and transmission values of cross dipole antenna elements. After training process, eight unknown resonator designs were tested and accurate results were obtained. Finally, one of the resonator planes, which was obtained from the artificial neural network, was fabricated and experimentally tested, then an accurate result was obtained. This study provides a good solution, especially for improving isolation in multiport antenna systems, using an artificial neural network approach.
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