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
Journal of Microwaves, Optoelectronics and Electromagnetic Applications(2021)
摘要
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.
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关键词
Multi-band FSS,5G,optimization,GRNN,MOCS
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