Autors: Singh H., Kumar V., Saxena K., Bonev, B. G.
Title: An Intelligent Model for prediction of Attenuation caused by Rain based on Machine Learning Techniques
Keywords: ITU model, Machine learning, Millimeter waves, Rain Attenuation, rainfall rate, regression, satellite communication

Abstract: The availability is the key performance matrix for the satellite communication system. There are various factors which affect the availability of links like hardware reliability, fading, interference etc. Attenuation caused by hydrometeors specially rain plays a significant role when dealing with frequencies above 10 GHz. Various models have been proposed in this regard but ITU-R model for rain attenuation is acceptable worldwide. This paper describes This paper proposed a comprehensive review on computational intelligence-based techniques for analysis and prediction of attenuation by the outdoor environments during designing of radio links. A modified intelligent prediction model based on machine learning is also proposed to predict the attenuation caused by rain.

References

    Issue

    2020 International Conference on Contemporary Computing and Applications, IC3A 2020, pp. 92–97, 2020, India, DOI: 10.1109/IC3A48958.2020.233277

    Цитирания (Citation/s):
    1. Learning-assisted rain attenuation prediction models - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus