Dual-Band Power Divider with Wide Suppression Band:

Golshan Mohamadpour; Salman Karimi; Saeed Roshani

doi:10.14500/aro.11945

Golshan Mohamadpour Department of Electrical Engineering, Lorestan University, Khorramabad, Iran https://orcid.org/0000-0002-1100-0626
Salman Karimi Department of Electrical Engineering, Lorestan University, Khorramabad, Iran https://orcid.org/0000-0001-9526-4508
Saeed Roshani Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran https://orcid.org/0000-0002-4024-2755

DOI: https://doi.org/10.14500/aro.11945

Keywords: Dual band Wilkinson power divider, Harmonic suppression, Neural network, Resonator

Abstract

In this paper, a planar dual-band Wilkinson power divider (DWPD) with a triangular-shaped resonator is designed. This work stands out from existing designs by addressing key limitations in conventional power dividers, i.e., physical size, harmonic suppression, and insertion loss. The proposed triangular shaped resonator has a compact size of 9.9 mm × 3.4 mm (0.26 λg × 0.09 λg ), where λg is electrical wavelength at 5.9 GHz, and provides a wide suppression band from 7.1 GHz to 20.6 GHz with a 20 dB attenuation level. In the proposed DWPD structure, two triangular shaped resonators are used in two branches. It works at 3.6 GHz and 5.5 GHz with <0.1 dB insertion loss at both operating bands. The input and output return losses and ports isolation parameters at both bands are better than 20 dB, which show good performance of the divider at operating bands. Besides the acceptable performance, the proposed DWPD provides a wide suppression band from 6.8 GHz to 20.5 GHz with more than 20dB attenuation level. In the divider design, the neural network is employed to model a triangular-shaped resonator. The proposed neural network has two outputs (S11 and S21), and two hidden layers with eight neurons at each layer. The weights of each neuron are obtained using particle swarm optimization algorithms. The proposed neural network model has accurate results, and the mean relative error of the train and test data for both outputs is <0.1 , which validates the accurate results of the proposed model.

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Author Biographies

Salman Karimi, Department of Electrical Engineering, Lorestan University, Khorramabad, Iran

Salman Karimi is an Assistant Professor of Electrical Engineering at Lorestan University in Khorramabad, Iran. He received his B.Sc. degree in Control Engineering from Sahand University of Technology (SUT) in 2006, and his M.Sc. and Ph.D. degrees in Communication Engineering from Tabriz University and SUT in 2008 and 2013, respectively. He has authored various publications in the areas of radio frequency and microwave engineering, signal processing, and machine learning. He serves as a reviewer for several journals published by IEEE, Elsevier, Springer, and other highly cited journals.

Saeed Roshani, Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

Saeed Roshani is an Associate Professor at the ‎Department of Electrical Engineering, Islamic Azad University, Kermanshah, Iran. He got the B.Sc. degree in Razi University, Kermanshah, Iran, the M.Sc. degree in Iran Shahed University, Tehran, Iran and the Ph.D. degree in, Razi University, Kermanshah, Iran. His research interests are in microwave circuits, passive and active devices, neural networks and artificial intelligence. Dr. Saeed was the Head of Faculty of Engineering, Islamic Azad University, Kermanshah Branch in 2018-2019.

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Dual-Band Power Divider with Wide Suppression Band

Artificial Intelligence Modeling for Performance Confirmation

Abstract

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References