Autors: Kumar V., Singh H., Saxena K., Bonev, B. G., Prasad R.
Title: An ANN Model for Predicting Radio Wave Attenuation due to Rain and its Business Aspect
Keywords: Rain Attenuation, Satellite Communication, ITU Model, Millimeter Waves, Clustering, Regression Analysis, ANN, Machine Learning

Abstract: In 2020, wireless providers should expect a 1,000-fold increase in mobile traffic, given the huge increase in demand for capacity in wireless data telecommunications every year. It forces researchers to look for new wireless spectrum that can handle high data rate demands. Next-generation technologies must address issues such as increased spectrum allocation in millimetre wave frequency bands, Creation of directional beam forming antennas, enhanced capacity for many simultaneous users, improved battery life, high data rates with decreased outage probability, lower infrastructure. The impact of rain on both satellite and terrestrial communications is discussed in this paper. An intelligent model based on ANN is proposed in this paper. The accuracy was 97.6% was observed in this model, which was better than another proposed model. Business aspect of proposed work was also discussed in this work.

References

    Issue

    29th National Conference with International Participation, TELECOM 2021, pp. 17-19, 2021, Bulgaria, DOI: 10.1109/TELECOM53156.2021.9659673

    Copyright ieee

    Вид: публикация в национален форум с межд. уч., публикация в реферирано издание, индексирана в Scopus