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<p>For 28&#xa0;GHz applications, a perturbed rectangular leading to a Plano-concave shaped patch has been designed by modifying the traditional rectangular patch. By deducting the semicircular patch from the square patch, the suggested patch design has been created. Based on the design frequency of 28&#xa0;GHz the perturbed patch’s radius is calculated that is same as that of guided wavelength. 27.6&#xa0;GHz has been found to be the resonant frequency and the return loss is -33.96 dB. The resonant behavior of the proposed plano concave geometry is analyzed using theoretical analysis, and further validated using machine learning techniques to predict the resonant frequency for the optimized antenna dimensions. Theoretical value, simulation outcome, measurement outcome, and findings from the machine learning approach have been compared. With a compact dimension of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:40\:\text{m}\text{m}\times\:40\:\text{m}\text{m}\:\times\:1.6\:\text{m}\text{m},\:\)</EquationSource> </InlineEquation>efficient utilization of this proposed antenna having can be done for 28&#xa0;GHz applications that includes 5G New Radio (NR) {(26.5–29.5&#xa0;GHz) and (27.5–28.35&#xa0;GHz)} millimeter-wave communication, automotive radar applications and satellite communication.</p>

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Analysis of a Perturbed Rectangular Patch Antenna with Machine Learning Tactics for 28 GHz Applications

  • 期刊论文

  • 发表日期：

    2026年1月26日

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  • Ribhu Abhusan Panda,
  • Asish Kumar Patnaik,
  • Neelamadhab Padhy

摘要

For 28 GHz applications, a perturbed rectangular leading to a Plano-concave shaped patch has been designed by modifying the traditional rectangular patch. By deducting the semicircular patch from the square patch, the suggested patch design has been created. Based on the design frequency of 28 GHz the perturbed patch’s radius is calculated that is same as that of guided wavelength. 27.6 GHz has been found to be the resonant frequency and the return loss is -33.96 dB. The resonant behavior of the proposed plano concave geometry is analyzed using theoretical analysis, and further validated using machine learning techniques to predict the resonant frequency for the optimized antenna dimensions. Theoretical value, simulation outcome, measurement outcome, and findings from the machine learning approach have been compared. With a compact dimension of \(\:40\:\text{m}\text{m}\times\:40\:\text{m}\text{m}\:\times\:1.6\:\text{m}\text{m},\:\) efficient utilization of this proposed antenna having can be done for 28 GHz applications that includes 5G New Radio (NR) {(26.5–29.5 GHz) and (27.5–28.35 GHz)} millimeter-wave communication, automotive radar applications and satellite communication.