Application of machine learning models for rainfall prediction and estimation of rain-induced attenuation for satellite communication in a tropical region

Abstract

The increasing demand for advanced technological equipment and high-capacity data transfer with enhanced signal quality necessitates the transition to higher frequency bands, particularly those beyond the congested Ku and Ka bands (11–40 GHz). Higher frequency signals offer longer travel distances, increased information-carrying capacity, reduced interference, and high data rates, crucial for meeting the growing demand for wireless communication services. However, these frequencies are susceptible to rain-induced attenuation, particularly in tropical regions like Nigeria, where precipitation significantly degrades signal quality and impacts satellite communication services. This study analyzes 50 years of monthly rainfall data (1962–2011) obtained from the Nigerian Meteorological Agency (NiMet) for five Nigerian locations: Port Harcourt, Calabar, Enugu, Ibadan, and Ikeja. The data was divided into five decades using a decadal scaling technique to investigate the long-term trends of precipitation effects on radio wave propagation. The Coefficient of Variation (CV) and Chebil's model were employed to analyze rainfall variability and deduce 1-min rainfall rates, respectively. CV was found to be predominant during July and August across the decades, indicating significant worst months for signal qualities over the region. The seasonal variation of rainfall rates was also examined, showing significant effects.SARIMA, ARIMA, Random Forest and SVM forecasting models have been tested toward the prediction of rainfall in Nigeria. The SVM performed better than the other tested models with the highest adjusted R² and least values of RMSE and MAE.The International Telecommunication Union's model (ITU-R P.618–14) was used to generate rain attenuation at Ku-band (12.275) GHz for the study locations. The findings confirm the reliability of Chebil's 1-min integration time rainfall rate model and validate decadal scaling as an effective method for developing mitigation measure for signal fading.