Dual-Band Power Divider with Wide Suppression Band

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 trian...

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Main Authors: Salman Karimi, Golshan Mohamadpour, Saeed Roshani
Format: Article
Language:English
Published: Koya University 2025-02-01
Series:ARO-The Scientific Journal of Koya University
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Online Access:http://88.198.206.215/index.php/aro/article/view/1945
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author Salman Karimi
Golshan Mohamadpour
Saeed Roshani
author_facet Salman Karimi
Golshan Mohamadpour
Saeed Roshani
author_sort Salman Karimi
collection DOAJ
description 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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issn 2410-9355
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publishDate 2025-02-01
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series ARO-The Scientific Journal of Koya University
spelling doaj-art-3675108949f2404e8b4023afe6ba7f382025-02-02T00:31:24ZengKoya UniversityARO-The Scientific Journal of Koya University2410-93552307-549X2025-02-0113110.14500/aro.11945Dual-Band Power Divider with Wide Suppression BandSalman Karimi0Golshan Mohamadpour1Saeed Roshani2Department of Electrical Engineering, Lorestan University, Khorramabad, IranDepartment of Electrical Engineering, Lorestan University, Khorramabad, IranDepartment of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran 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. http://88.198.206.215/index.php/aro/article/view/1945Dual band Wilkinson power dividerHarmonic suppressionNeural networkResonator
spellingShingle Salman Karimi
Golshan Mohamadpour
Saeed Roshani
Dual-Band Power Divider with Wide Suppression Band
ARO-The Scientific Journal of Koya University
Dual band Wilkinson power divider
Harmonic suppression
Neural network
Resonator
title Dual-Band Power Divider with Wide Suppression Band
title_full Dual-Band Power Divider with Wide Suppression Band
title_fullStr Dual-Band Power Divider with Wide Suppression Band
title_full_unstemmed Dual-Band Power Divider with Wide Suppression Band
title_short Dual-Band Power Divider with Wide Suppression Band
title_sort dual band power divider with wide suppression band
topic Dual band Wilkinson power divider
Harmonic suppression
Neural network
Resonator
url http://88.198.206.215/index.php/aro/article/view/1945
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AT golshanmohamadpour dualbandpowerdividerwithwidesuppressionband
AT saeedroshani dualbandpowerdividerwithwidesuppressionband