Browsing by Author "Mohammed, Chetioui"

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Citation - Scopus: 1
Designing Cross-Coupled Microstrip Bandpass Filter Based Coupling Matrix Optimization Technique
(Society for Microwave Technique Technologies and System, 2024) Mehdi Damou; Mohammed Chetioui; Mustafa Seçmen; Abdelhakim Boudkhil; Gouni Slimane; Abdelhakim, Boudkhil; Mohammed, Chetioui; Secmen, Mustafa; Slimane, Gouni; Mehdi, Damou
This research article presents a novel compact cross-coupled bandpass filter (BPF) microstrip operating at 1.2 GHz. The proposed filter is designed and developed by coupling the RLC resonator and TL transmission line circuits excited by a symmetrical microstrip feed line (MSL). The fractional bandwidth (FBW) of the filter is found to be 12.83%. The equivalent lumped circuit model of the filter is obtained from AWR Designer. By decomposing the filter into separate entities for individual electromagnetic (EM) simulation via the High Frequency Structure Simulator (HFSS) and the equivalent lumped circuit model of the filter is obtained in AWR designer this approach achieves computational efficiency facilitating the extraction of key parameters aligned to specified general coupling matrix (CM). All these parameters from the overall response of the filter are used in the Chebychev approximation method models at the second and fourth order. The transmission zeros are close to the bandpass edge. The proposed filter has a reflection loss(|S11|) less than -25 dB and an insertion loss (-|S21|) less than 0.21dB. Besides the filter has strong and varying group delay response over the entire bandwidth from 1.15 GHz to 1.3 GHz. The proposed bandpass filter also shows good stopband rejection (being greater than 25 dB) and |S11|< -0.1 dB from 1.35 GHz to 1.75 GHz and sharp decrease in bandwidth at the hard shoulder. All simulated results are extracted via the HFSS simulator method based on finite element FEM. All results produced by AWR design software have a close similarity with the results simulated and optimized by HFSS. © 2024 Elsevier B.V. All rights reserved.
Predicting S-Parameters in Microstrip Trisection Passband Filter Using a S-KNN Algorithm
(International Academy of Microwave and Optical Technology (IAMOT), 2024) Senasli Lamia; Mohammed Chetioui; Mehdi Damou; Senasli Nour El Houda Sarah; Abdelhakim Boudkhil; Mustafa Seçmen; Abdelhakim, Boudkhil; Mohammed, Chetioui; Lamia, Senasli; Secmen, Mustafa; Sarah, Senasli Nour El Houda; Mehdi, Damou
In the field of microwave modelling and design the Supervised K-Nearest Neighbor (S-KNN) algorithm has emerged as a valuable tool. An S-KNN based approach to the modelling of passband trisection filter components with emphasis on the optimization of the hyperparameter K is presented in this paper. Our technique introduces a novel S-KNN topology specifically designed for parametric modeling of microwave components with S-parameters as outputs. Unlike previous methods which often rely on manual parameter tuning or lack robust hyperparameter optimization our optimized S-KNN model achieves high accuracy (0.9429) and low mean squared error (0.0109) by tuning K to the specific dataset. The study compares various distance metrics and employs Euclidean distance for predictions. Results demonstrate that the optimized S-KNN model achieves strong alignment with electromagnetic (EM) simulations with an average accuracy of 94.29% offering a faster and potentially more efficient alternative to traditional design techniques. © 2024 Elsevier B.V. All rights reserved.