Signal Attenuation Prediction Model for a 22 GHz Terrestrial Communication Link in Sudan Due to Dust and Sand Storms Using Machine Learning

Signal attenuation due to dust and sand storms is one of the major problems in the utilization of microwave frequency bands for terrestrial and space communication especially in arid regions such as Northern Africa and Middle Eastern regions. In this paper, a machine learning (ML) model is developed...

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Bibliographic Details
Published in:	IEEE access Vol. 9; pp. 164632 - 164642
Main Authors:	Shamim, Mohammed Zubair M., Elsheikh, Elfatih Abdelrahman Ahmed, Salih, Fakher Eldin Mohamed Suliman, Islam, Md Rafiqul
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Arid regions Atmospheric attenuation Atmospheric measurements Atmospheric modeling Attenuation Dust and sand storms Dust storms Humidity Machine learning Meteorological data Microwave attenuation Microwave communication Microwave frequencies Microwave measurement microwave signal attenuation Prediction models Relative humidity Sand Space communication Storms terrestrial communication Visibility Wind speed Sudan
Online Access:	Get full text
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