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Smart Channel Modelling for Cloud and Fog Attenuation Using ML for Designing of 6G Networks at D and G Bands

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  • Hitesh Singh, Aarhus Universitet, University of Lucknow
  • ,
  • Vivek Kumar
  • Kumud Saxena, Aarhus Universitet, University of Lucknow
  • ,
  • Vinod M. Kapse, Aarhus Universitet
  • ,
  • Boncho Bonev, Technical University of Sofia
  • ,
  • Ramjee Prasad

In case of future telecommunication technologies, extremely high data rates above 100 Gbps is the expectations, which can be fulfilled by utilizing higher spectrum bands. Higher frequency bands like terahertz wave bands are expected to have far broader bandwidths then 5G, therefore 6G will need to encourage R&D activities to utilize so called terahertz waves with frequencies ranging from 100 to 200 GHz. The challenge in utilizing these higher frequency bands is their sensitive nature toward outdoor environmental conditions like cloud, Fog, dust and Rain. To address these issues, this paper proposes a Machine Learning Model based on Artificial Neural Network to predict the attenuation caused due to Clouds and Fog at D and G bands. The model was trained using AMSER–2 Satellite data. The trained model is further optimized using different optimizing techniques. Obtained results was compared with the different existing models.

TidsskriftWireless Personal Communications
Sider (fra-til)1669-1692
Antal sider24
StatusUdgivet - apr. 2023

Bibliografisk note

Funding Information:
This work was not supported by the financial Grant from any organization.

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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