Department of Business Development and Technology

Approximations for ITV Rain Model Using Machine Learning

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Vivek Kumar, Noida Institute of Engineering and Technology
  • ,
  • Hitesh Singh, Noida Institute of Engineering and Technology
  • ,
  • Kumud Saxena, Noida Institute of Engineering and Technology
  • ,
  • Boncho Bonev, Technical University of Sofia
  • ,
  • Ramjee Prasad

In communication technologies, availability is the key performance matrix. Different factors which affect the availability of links are hardware reliability, finding interference etc. In radio wave propagation studies, attenuation caused by hydrometeors like rain plays an important role especially for higher frequency bands. Different models are there for the prediction of attenuation caused by rain out of which ITU-R model is one of the widely acceptable models. In this paper, K-Means algorithm is used to propose an improved ITU-R model. Proposed model can make up the shortcoming of ITU-R model to determine the break-up points in frequency range and obtained soft clusters have been trained by machine learning algorithms then proposes a mathematical model for prediction of radio wave attenuation due to rain. Results from proposed model compared with ITU-R model.

Original languageEnglish
Title of host publication2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2021 - Proceedings
Number of pages4
PublisherIEEE
Publication year2021
Pages159-162
ISBN (Electronic)9781665428873
DOIs
Publication statusPublished - 2021
Event56th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2021 - Sozopol, Bulgaria
Duration: 16 Jun 202118 Jun 2021

Conference

Conference56th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2021
LandBulgaria
BySozopol
Periode16/06/202118/06/2021
Series International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)
Volume56th

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

    Research areas

  • Clustering, ITU model, Millimeter waves, Rain Attenuation, Regression analysis

See relations at Aarhus University Citationformats

ID: 224425753