Adaptive Millimeter Wave Channel Switching Based on Real-Time Weather Data Using Fuzzy Logic Control

Millimeter wave (mmWave) communication systems offer high data rates, but these systems are highly susceptible to environmental factors, particularly weather conditions such as rain, dust, and sand. This paper presents a novel approach to enhance the reliability of mmWave communication by implementing a Fuzzy Controller System (FCS) for dynamic channel switching. The proposed system integrates real-time measured weather data, such as rain rate, with the fuzzy logic controller to intelligently select the optimum frequency channel with the least attenuation under current atmospheric conditions. The fuzzy controller makes adaptive switching decisions by continuously analyzing environmental changes to maintain signal quality and system performance. Experimental results and simulations demonstrate that incorporating real measured data significantly improves the system’s ability to respond to weather variability, ensuring stable and efficient mmWave communication. This work provides a practical framework for implementing intelligent, weather-aware channel-switching mechanisms in next-generation wireless communication networks.

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Publication Details

Journal
IEEE Journal of Radio Frequency Identification
Published
2025-01-01
DOI
https://doi.org/10.1109/jrfid.2025.3575098
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.00

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Adaptive Millimeter Wave Channel Switching Based on Real-Time Weather Data Using Fuzzy Logic Control

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Adaptive Millimeter Wave Channel Switching Based on Real-Time Weather Data Using Fuzzy Logic Control

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article en

Abstract

Millimeter wave (mmWave) communication systems offer high data rates, but these systems are highly susceptible to environmental factors, particularly weather conditions such as rain, dust, and sand. This paper presents a novel approach to enhance the reliability of mmWave communication by implementing a Fuzzy Controller System (FCS) for dynamic channel switching. The proposed system integrates real-time measured weather data, such as rain rate, with the fuzzy logic controller to intelligently select the optimum frequency channel with the least attenuation under current atmospheric conditions. The fuzzy controller makes adaptive switching decisions by continuously analyzing environmental changes to maintain signal quality and system performance. Experimental results and simulations demonstrate that incorporating real measured data significantly improves the system’s ability to respond to weather variability, ensuring stable and efficient mmWave communication. This work provides a practical framework for implementing intelligent, weather-aware channel-switching mechanisms in next-generation wireless communication networks.

IEEE Journal of Radio Frequency IdentificationVol. 9
University of South Carolina (US), Benedict College (US), Ecpi University (US), North Carolina Agricultural and Technical State University (US), Clemson University (US)
National Science Foundation
Climate action, Affordable and clean energy
Openalex Percentile: Top 90%
Millimeter-Wave Propagation and Modeling
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