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Review of State-of-the-Art Microwave Filter Tuning Techniques and Implementation of a Novel Tuning Algorithm Using Expert-Based Hybrid Learning

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A Correction to this article was published on 01 January 2024

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Abstract

Present-day demand and supply of connectivity necessitate the rapid production of Microwave (MW) filter units. The production of these filters is then followed by the step of utmost importance in the assembly line, viz., the ‘tuning of the filter’, as tuning is crucial to meeting the selectivity requirements of the band. Since the advent of filters, tuning has always been done manually, and hence it is considered a bottleneck by experts in the field. Thus, the need to automate the system is highly implied. The goal of the current work is to outline various MW filter tuning techniques that have been advocated by the community of researchers. The limitations of the said research works and their comparative analysis are also encapsulated in tabular form in the present paper. The paper ends with the implementation of an Expert-Based Hybrid Deep Learning Algorithm to fully automate the filter tuning process.

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It is an extensive literature survey paper with an implementation of a novel approach. All required data has been mentioned in the manuscript and no other data is required.

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Funding

Research was supported by Tallinn University of Technology, Tallinn, Estonia.

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Authors and Affiliations

  1. Tallinn University of Technology, Tallinn, Estonia

    Even Sekhri & Mart Tamre

  2. Delhi Technological University, Delhi, India

    Rajiv Kapoor

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  1. Even Sekhri
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  2. Rajiv Kapoor
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Contributions

The conceptualization of this paper was a collaborative effort among all three authors. The first author conceived the idea of paper; developed, tested, and validated the novel tuning algorithm; and compiled the manuscript. The second author provided the vision for the novel expert-based hybrid learning algorithm and also contributed to testing, and multiple reviews. The third author was part of the overall execution of the objective.

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Correspondence to Rajiv Kapoor.

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The original version of this article was revised: The institute name was corrected for authors Even Sekhri and Mart Tamre, and the funding and author contribution sections were corrected.

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Sekhri, E., Kapoor, R. & Tamre, M. Review of State-of-the-Art Microwave Filter Tuning Techniques and Implementation of a Novel Tuning Algorithm Using Expert-Based Hybrid Learning. Wireless Pers Commun 134, 625–681 (2024). https://doi.org/10.1007/s11277-024-10894-x

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