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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Koya University
2025-02-01
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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 |
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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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format | Article |
id | doaj-art-3675108949f2404e8b4023afe6ba7f38 |
institution | Kabale University |
issn | 2410-9355 2307-549X |
language | English |
publishDate | 2025-02-01 |
publisher | Koya University |
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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 |
work_keys_str_mv | AT salmankarimi dualbandpowerdividerwithwidesuppressionband AT golshanmohamadpour dualbandpowerdividerwithwidesuppressionband AT saeedroshani dualbandpowerdividerwithwidesuppressionband |