Adjustment of the ITU-R Model for the Rainfall Attenuation Prediction in Satellite Links, by Applying Industry X.0 Base Technology

• Main Authors: Pinto-Mangones, Angel D., Perez-Garcia, Nelson A., Castillo-Rondon, Jordi J., Castillo-Sanchez, Jesus A., Torres-Tovio, Juan M., Ibarra-Hernandez, Frank A., Rivera-Julio, Yair E., Yepes Escobar, Jorge A.
• Format: Conference Proceeding
• Language: English
• Subjects: Attenuation; Computational modeling; Industries; ITU; Media; Particle swarm optimization; Predictive models; Rain; Rain attenuation modeling; RMSE value; Satellite communication systems; Satellites; Vectors
• ISSN: 2771-568X
• DOI: 10.1109/COLCOM62950.2024.10720256

Since the existing models in the literature for the prediction of rain attenuation in satellite links operating at frequencies above 10 GHz do not always correlate with the climatic characteristics of the location of interest and/or with the technical characteristics of the link to be implemented, there is a permanent need to develop rain attenuation models that increase the probability of finding one or more models with the highest possible correlation to the aforementioned characteristics. In this sense, in this letter it is developed a new model for the estimation of the mentioned attenuation using one of the base technologies of Industry X.0, specifically artificial intelligence, to tune the ITU rain fading model (contained in Recommendation ITU-R P.618-14) to a set of measurements of the referred attenuation reported in the literature. The comparison of the performance of the new model with that of the original ITU model, in the prediction of rain attenuation for the links considered in the development of the work, show a notorious improvement, in terms of the root mean square error (RMSE), with reductions from 26.85% to 73.05%, in the case of individual links, and 46.8%, for the totality of the links.