Tri-Band, Stable and Compact Patch Frequency Selective Surface Optimized via Hybrid Bioinspired Computing for Applications at 2.4, 3.5 and 5.8 GHz

• Autor(a) principal: Ferreira,Flávio H. C. S.
• Data de Publicação: 2021
• Outros Autores: Araújo,Jasmine P. L., Gomes Neto,Alfredo, Coutinho,Ianes B. G., Barros,Fabrício J. B., Cavalcante,Gervásio P. S., Alcântara Neto,Miércio C. de
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Journal of Microwaves. Optoelectronics and Electromagnetic Applications
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742021000300570
• topic: Multi-band FSS; 5G; optimization; GRNN; MOCS

Abstract This work addresses the synthesis of a multi-band frequency selective surface (FSS) through bioinspired computing and a general regression neural network (GRNN). This hybrid computational method, which utilizes the multi-objective cuckoo search algorithm combined to a GRNN, determine the best physical dimensions of the FSS in order to achieve a multi-band filtering at the 2.4, 3.5 and 5.8 GHz spectrums. Therefore, the results are to be applied to aid the propagation of Wi-Fi, WLAN, WiMAX and future sub-6 GHz 5G systems. The resonant frequencies were measured and a -10 dB cutoff value has been considered for the transmission coefficient. The triple rectangular loop conductor geometry of the device is printed upon a glass epoxy (FR-4) substrate. Measurements were made for different wave incidence angles, from 0° up to 45°, to demonstrate how signal incidence would affect the device’s functioning. The agreement between simulated and measured data display satisfactory results.