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Transfer of Technologies for Performance Degradation Prediction and Channel Switching in Vehicular Networks Under Harsh Weather Conditions and Integration with State-of-the-Art Products
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2024-09-01
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[PDF-1.94 MB]
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Edition:Final Report (10/01/2023 - 09/30/2024)
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Abstract:The 5G millimeter wave (mm-Wave) technology has revolutionized modern communication systems with significantly increased data transmission speeds and bandwidth. Despite these advancements, environmental conditions profoundly impact mm-wave signals, particularly in areas prone to dust and sandstorms. These storms, characterized by high concentrations of suspended particles, cause considerable signal attenuation and degradation. This report discusses the development of predictive mathematical models that estimate mm-wave signal degradation under dust and sandstorm conditions. These models incorporate critical factors such as dust particle size distribution, storm intensity, signal frequency, and atmospheric conditions. Addressing the challenges posed by environmental factors, we introduce a Fuzzy Controller for adaptive mm-wave channel switching. This controller leverages advanced algorithms to facilitate smooth and efficient frequency transitions, enhancing signal reliability. Our approach goes beyond conventional solutions that switch between frequencies based solely on signal strength. Instead, it intelligently integrates environmental data, such as visibility and rain intensity, to select optimally from five distinct frequencies, thereby improving the adaptability and effectiveness of 5G networks in adverse weather conditions.
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