An ANN Model for predicting Radio Wave Attenuation due to Rain and its Business Aspect

被引:1
作者
Kumar, Vivek [1 ]
Singh, Hitesh [1 ]
Saxena, Kumud [1 ]
Bonev, Boncho [2 ]
Prasad, Ramjee [3 ]
机构
[1] Noida Inst Engn & Technol, Greater Noida, India
[2] Tech Univ Sofia, Dept Radiocommun & Videotechnol, Sofia, Bulgaria
[3] Aarhus Univ, Future Technol Business Ecosyst Innovat, Herning, Denmark
来源
2021 29TH NATIONAL CONFERENCE WITH INTERNATIONAL PARTICIPATION (TELECOM) | 2021年
关键词
Rain Attenuation; Satellite Communication; ITU Model; Millimeter Waves; Clustering; Regression Analysis; ANN; Machine Learning;
D O I
10.1109/TELECOM53156.2021.9659673
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:17 / 19
页数:3
相关论文
共 11 条
[1]   Rain Attenuation Prediction Using Artificial Neural Network for Dynamic Rain Fade Mitigation [J].
Ahuna, M. N. ;
Afullo, T. J. ;
Alonge, A. A. .
SAIEE AFRICA RESEARCH JOURNAL, 2019, 110 (01) :11-18
[2]  
Alencar G. A., 2004, 2004 Asia-Pacific Radio Science Conference Proceedings (IEEE Cat. No.04EX825), P344, DOI 10.1109/APRASC.2004.1422479
[3]   Implementation of Artificial Neural Network for Prediction of Rain Attenuation in Microwave and Millimeter Wave Frequencies [J].
Amarjit ;
Gangwar, R. P. S. .
IETE JOURNAL OF RESEARCH, 2008, 54 (05) :346-352
[4]  
[Anonymous], 2014, P 2 INT C COMM SIGN
[5]  
*ITU R, 2007, P6189 ITUR
[6]  
Li TS, 2015, 2015 IEEE 16TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT), P615, DOI 10.1109/ICCT.2015.7399913
[7]   Rain Attenuation Along Terrestrial Millimeter Wave Links: A New Prediction Method Based on Supervised Machine Learning [J].
Livieratos, Spiros N. ;
Cottis, Panayotis G. .
IEEE ACCESS, 2019, 7 :138745-138756
[8]  
Mpoporo L. J., 2019, P 2019 INT MULTIDISC, P1
[9]   Attenuation prediction for fade mitigation using neural network with in situ learning algorithm [J].
Roy, Bijoy ;
Acharya, Rajat ;
Sivaraman, M. R. .
ADVANCES IN SPACE RESEARCH, 2012, 49 (02) :336-350
[10]  
Singh Hitesh, 2020, 2020 International Conference on Contemporary Computing and Applications (IC3A), P92, DOI 10.1109/IC3A48958.2020.233277