ANN: A Deep Learning Model for Prediction of Radio Wave Attenuation Due to Clouds

Extremely high data rates above 100 Gbps are expected in future communications technologies, which can be achieved by exploiting higher spectrum bands. Higher frequency bands, such as millimeter wave bands, are predicted to have far wider bandwidths hence 6G will need to promote R&D to use millimeter waves with frequencies ranging from 20 to 100 GHz. The use of these higher frequency bands is complicated by their sensitivity to external ambient conditions such as cloud, fog, dust, and rain. This paper presents a Machine Learning based cloud attenuation model with global applicability. With improved accuracy the Artificial Neural Network (ANN) based model is developed by using real time data set from the AMSER—2 satellite at Indian site. A comparative analysis is carried out in the results and discussion section.