Design and Synthesis of an Ultra Wide Band FSS for mm-Wave Application via General Regression Neural Network and Multiobjective Bat Algorithm

• Published in: Journal of Microwaves, Optoelectronics and Electromagnetic Applications Vol. 18; no. 4; pp. 530 - 544
• Main Authors: Neto, Miércio C. A., Araújo, Jasmine P. L., Mota, Raimundo J. S., Barros, Fabrício J. B., Ferreira, Flávio H. C. S., Cavalcante, Gervásio P. S., Castro, Bruno S. L.
• Format: Journal Article
• Language: English
• Published: Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo 01.12.2019; Sociedade Brasileira de Microondas e Optoeletrônica; Sociedade Brasileira de Eletromagnetismo
• Subjects: ENGINEERING, ELECTRICAL & ELECTRONIC; Frequency Selective Surfaces (FSS); general regression neural network (GRNN); hybrid technique; multiobjective bat algorithm (MOBA); OPTICS; general regression neural network (GRNN); multiobjective bat algorithm (MOBA); hybrid technique; Frequency Selective Surfaces (FSS)
• ISSN: 2179-1074; 2179-1074
• DOI: 10.1590/2179-10742019v18i41729

Abstract In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient's scattering matrix (dB), were obtained at the cutoff threshold at −10dB, to control the bandwidth of the device.