Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1941
Title: Low Profile Dual Band H-Slotted DGS Based Antenna Design Using ANN for K/Ku Band Applications
Authors: Nakmouche, Mohammed Farouk
Allam, A. M. M. A.
Fawzy, Diaa E.
Lin, Ding Bing
Keywords: microstrip antenna
defected ground structure (DGS)
finite element methods
artificial neural networks (ANN)
CST studio suite
5G band
dual band
low profile
Array
Publisher: IEEE
Abstract: In this manuscripts, H-slotted DGS based antenna configuration for K/Ku applications is designed, fabricated and measured using ROHDE & SCHWARZ ZVB20 network analyzer. Simulation studies are performed using Electromagnetic Simulation Software CST Studio Suite. Moreover, a development of Artificial Neural Networks (ANN) model is implemented based on feed-forward back-propagation and Bayesian regularization learning algorithm. The optimal position for H-slotted DGS antenna performance is predicted in terms of reflection coefficient and resonance frequency. The antenna is implemented on Rogers RT/Duroid 5880 with relative dielectric constant of 0.0009 and thickness 0.38 mm. It operates at both 15.04 GHz (from 14.87 GHz to 15.208 GHz) and 24.77 GHz (from 24.404 GHz to 25.137 GHz). The antenna achieves gains of 5.59 dB and 6.10 dB and efficiencies of 87 % and 80 % at both frequencies, respectively. The simulation using CST, predicted ANN and measurement results are in good agreement.
Description: 8th International Conference on Electrical and Electronics Engineering (ICEEE) -- APR 09-11, 2021 -- Antalya, TURKEY
URI: https://doi.org/10.1109/ICEEE52452.2021.9415911
https://hdl.handle.net/20.500.14365/1941
ISBN: 978-1-6654-4071-4
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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