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In this paper, a predictive approach for calculating the return loss of a slotted square patch antenna with a defective ground structure (SSPA-DGS) designed for energy-harvesting applications in smart cities is introduced. The strategy makes use of the Gaussian Process Regression (GPR). The designed antenna works from 1.7 to 3.2 GHz. We varied the antenna internal slot radius Ra, patch length la, thickness t, and dielectric constant of the antenna. A total of 125 data samples were taken from the simulation using HFSS software, and all the samples were used in ML models. For validation, 25 data samples are used to test the prepared models for the GPR. The data is compared with the simulated return loss data. The predicted return loss of GPR model has an average error of −0.041785325.

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Return Loss Prediction of Square Patch Antenna with Defective Ground Structure for RF Energy Harvesting in Smart Cities Using GPR

  • 会议论文

  • 发表日期：

    2025年

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  • Bujjibabu Nannepaga,
  • S. Varadarajan

摘要

In this paper, a predictive approach for calculating the return loss of a slotted square patch antenna with a defective ground structure (SSPA-DGS) designed for energy-harvesting applications in smart cities is introduced. The strategy makes use of the Gaussian Process Regression (GPR). The designed antenna works from 1.7 to 3.2 GHz. We varied the antenna internal slot radius Ra, patch length la, thickness t, and dielectric constant of the antenna. A total of 125 data samples were taken from the simulation using HFSS software, and all the samples were used in ML models. For validation, 25 data samples are used to test the prepared models for the GPR. The data is compared with the simulated return loss data. The predicted return loss of GPR model has an average error of −0.041785325.