Browsing by Author "Nakmouche, Mohammed F."

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Citation - WoS: 3
Citation - Scopus: 6
Design and Measurement of Triple H-Slotted Dgs Printed Antenna With Machine Learning
(Emw Publishing, 2021) Nakmouche, Mohammed F.; Allam, Abdemegeed M. M. A.; Fawzy, Diaa E.; Abdalla, Mahmoud A.
This paper presents the design and measurements of a dual-band Triple H-Defected Ground Structure (Triple H-DGS) antenna. DGS has proven to be successful in the design of multiband antennas; however because of the lack of a standard approach, the determination of the exact position of the Triple H-DGS requires rigorous and lengthy numerical computations. The aim of the current work is to present a state-of-the-art innovative, efficient, and accurate solution based on Machine Learning (ML) techniques. The design is based on Substrate Integrated Waveguide (SIW) technology which provides low cost, small size, and convenient integration with planar circuits. The antenna is fabricated on a Roger 5880 substrate with a thickness of 1.6 mm, relative dielectric constant of 2.2, and tangent loss of 0.0009. The proposed antenna was developed using a hybrid solution based on CST Microwave Studio assisted by ML, and the fabricated prototype was measured using both ROHDE & SCHWARZ ZVB20 network analyser and an anechoic chamber setting. The measurement results show good agreement with the simulation. The antenna demonstrates a dual-band performance at centre frequencies of 12.67 GHz and 14.56 GHz, for which the respective antenna gains are 7.03 dBi and 7.38 dBi, and antenna directivities of 7.77 dB and 8.13 dB, respectively. The antenna total efficiencies are 95.25% and 95.60%, at the corresponding centre frequencies. The developed ML based technique shows good accuracies of about 98% in the determination of the DGS position and saves more than 99% of the computational time. The developed antenna is compact, simple in structure, and can be used for different applications in the Ku band.
Citation - Scopus: 7
A Novel Dual-Band Printed Siw Antenna Design Based on Fishnet & Ccrr Dgs Using Machine Learning for Ku-Band Applications
(Electromagnetics Academy, 2021) Nakmouche M.F.; Magray M.I.; Allam A.M.; Fawzy D.E.; Lin D.B.; Tarng J.-H.; Fawzy, Diaa E.; Nakmouche, Mohammed F.; Magray, Muhammad I.; Allam, Abdemegeed M.; Lin, Ding Bing; Tarng, Jenn-Hwen
—This paper analyzes and solves the complexity to determine the optimum positions of the Fishnet & Complementary Circular Ring Resonator (CCRR) based Defected Ground Structures (DGS) for Substrate Integrated Waveguide (SIW) based antennas. A new state-of-art technique based on Artificial Neural Network (ANN)-Machine Learning (ML) is proposed for overcoming the lack of solid and standard formulations for the computation of this parameter related to a targeted frequency. As a proof of concept and to test the performance of our approach, the algorithm is applied for the determination of the CCRR and Fishnet-DGS’s optimal positions for a SIW based antenna. The SIW technique provides the advantages of low cost, small size, and convenient integration with planar circuits. The ANN-ML based technique is optimized to attain dual-band resonances with optimal gain and radiation efficiency. The simulation results of the first Fishnet-DGS based antenna show good minimum return losses at two center frequencies, namely, 16.6 GHz (with gain of 6 dB and radiation efficiency of 95%) and 17.7 GHz (with gain and radiation efficiency of 9 dB and 96%, respectively). The second CCRR-DGS based antenna shows about 8 dB gain and a radiation efficiency of 87% at 17.3 GHz, and gain and efficiency of about 8.5 dB and 85% are observed at 17.8 GHz. The proposed CCRR and Fishnet-DGS based antenna are low profiles, low costs, with good gains and radiation efficiencies, making both designs very suitable for Ku-band applications. There is a fair agreement between the measured and simulated results. The achieved dual-band resonances act as a proof of concept that the proposed ANN-ML techniques can be employed for the determination of the optimal positions for CCRR and Fishnet thereby attaining any target dual-bands in the Ku-band with good accuracy of about 98% and a save of 99% in the overall the computational time. © 2021, Electromagnetics Academy. All rights reserved.