Computational Intelligent method for Cloud Layer Classification using Millimeter Wave Technology for Designing of 6G Network

Extremely high data rate communication with a peak data rate above 100 Gbps is expected to be supplied in sixth-generation (6G) mobile communication systems by utilizing higher frequency bands like millimeter-wave bands such as 28 GHz and above. Higher frequency bands, such as millimeter wave, are expected to have far broader bandwidth than 5G, therefore 6G will need to encourage R&D activities. There are basic difficulties in the millimeter wave, such as increased recti linearity and path loss than in the 28 GHz spectrum. In case of satellite communication atmospheric attenuation plays a crucial role in designing the network. Different studies have been done in regards to predict attenuation due to clouds but main problem is the complex structure of clouds. This paper proposes the methodology to classify the cloud layer using different machine learning techniques. Using signal strength and frequency cloud layer is classified. Promising results are obtained in the implementation of the model.