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Design and Modeling of a Compact Power Divider with Squared Resonators Using Artificial Intelligence

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Abstract

In this paper, a novel miniaturized microstrip Wilkinson power divider (WPD) using squared resonators and open-ended stubs is designed, fabricated, and measured. The proposed divider is designed at 1.9 GHz, which suppresses 2nd, 3rd, and 4th harmonics with high attenuation levels. Moreover, the size of the proposed divider is only 0.1 λg × 0.07  λg, which reduces the circuit size by more than 55%, compared to the conventional Wilkinson divider. In the design process, the neural network model and LC-equivalent circuit model are used to predict the transmission zeros of the circuit. These transmission zeros are used to provide the suppression at the desired harmonics. Also, the main circuit elements could be predicted with the neural network model, which results in a performance improvement of the proposed divider. The results show that the proposed model can predict the frequency response of the designed WPD, accurately.

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Acknowledgements

This research has been supported by the Ministry of Education, Youth and Sports of the Czech Republic under the Project OP VVV Electrical Engineering Technologies with High-Level of Embedded Intelligence CZ.02.1.01/0.0/0.0/18_069/0009855.

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Authors and Affiliations

  1. Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

    Saeed Roshani, Farzad Mohebi & Sobhan Roshani

  2. Research and Innovation Center for Electrical Engineering (RICE), University of West Bohemia, Pilsen, Czech Republic

    Mohammad Behdad Jamshidi

  3. Department of Power Electronics and Machines (KEV), University of West Bohemia, Pilsen, Czech Republic

    Mohammad Behdad Jamshidi

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  1. Saeed Roshani
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  2. Mohammad Behdad Jamshidi
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  4. Sobhan Roshani
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Correspondence to Sobhan Roshani.

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Roshani, S., Jamshidi, M.B., Mohebi, F. et al. Design and Modeling of a Compact Power Divider with Squared Resonators Using Artificial Intelligence. Wireless Pers Commun 117, 2085–2096 (2021). https://doi.org/10.1007/s11277-020-07960-5

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  • DOI: https://doi.org/10.1007/s11277-020-07960-5

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