Estimation of 28 GHz Band Wave Propagation using Machine Learning

This paper presents estimation of 28 GHz band wave propagation using machine learning. Electromagnetic waves in millimeter wave (mmWave) band, such as 28 and 39 GHz, are used for 5G communications. Because electromagnetic waves in the mmWave band are affected by obstructions, estimation of radio propagation is necessary. In this study, we use machine learning to estimate the wave propagation of electromagnetic waves in the 28 GHz band in order to estimate the effect of obstacles. The analytical model and results obtained by the ray tracing method was used as the training data for the machine learning. The results obtained by the convolutional neural network yielded good estimates. Its coefficient of determination was 0.91.

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Publication Details

Journal
International Journal of Applied Electromagnetics and Mechanics
Published
2025-05-25
DOI
https://doi.org/10.1177/13835416251345611
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
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article

Estimation of 28 GHz Band Wave Propagation using Machine Learning

Keiichi Ueda, Y. Watanabe
International Journal of Applied Electromagnetics and Mechanics
Millimeter-Wave Propagation and Modeling
article

Estimation of 28 GHz Band Wave Propagation using Machine Learning

Keiichi Ueda, Y. Watanabe
article en

Abstract

This paper presents estimation of 28 GHz band wave propagation using machine learning. Electromagnetic waves in millimeter wave (mmWave) band, such as 28 and 39 GHz, are used for 5G communications. Because electromagnetic waves in the mmWave band are affected by obstructions, estimation of radio propagation is necessary. In this study, we use machine learning to estimate the wave propagation of electromagnetic waves in the 28 GHz band in order to estimate the effect of obstacles. The analytical model and results obtained by the ray tracing method was used as the training data for the machine learning. The results obtained by the convolutional neural network yielded good estimates. Its coefficient of determination was 0.91.

International Journal of Applied Electromagnetics and MechanicsVol. 79(2)
Tokyo Metropolitan Industrial Technology Research Institute (JP)
Openalex Percentile: Top 90%
Millimeter-Wave Propagation and Modeling
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