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Machine learning (ML) has become prime in various industries because it is filled with various and abundant data and has excellent processing. Present-day research underlines its importance in today’s technology. The paper focuses on machine learning algorithms in antenna design as well as learning algorithms. Also, it looks for the basic differences between AI and machine learning, and the wide range of their technological approaches. It also compares the outcomes of machine learning in antenna design with those of traditional methods. The ML study shows that the random forest algorithm provides the best prediction results. A circular patch antenna is designed and fabricated using a coaxial feed that operates at 6.15 GHz. The antenna with a 15 percent bandwidth and 8.5 dBi gain is measured.

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Design and Optimization of a 6 GHz Circular Patch Antenna Using Machine Learning Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • Kalyani Bobade,
  • Ankita H. Harkare,
  • Ishika Patne,
  • Anshika Jain,
  • Bhumika Neole,
  • Vaijyanti H. Panse

摘要

Machine learning (ML) has become prime in various industries because it is filled with various and abundant data and has excellent processing. Present-day research underlines its importance in today’s technology. The paper focuses on machine learning algorithms in antenna design as well as learning algorithms. Also, it looks for the basic differences between AI and machine learning, and the wide range of their technological approaches. It also compares the outcomes of machine learning in antenna design with those of traditional methods. The ML study shows that the random forest algorithm provides the best prediction results. A circular patch antenna is designed and fabricated using a coaxial feed that operates at 6.15 GHz. The antenna with a 15 percent bandwidth and 8.5 dBi gain is measured.