A Signal Strength Fluctuation Prediction Model Based on Symbolic Regression

被引：0
|
作者：
Gajdos, Petr [1 ,2 ,4 ]
Dohnalek, Pavel [1 ,2 ]
Sebesta, Roman [1 ,3 ]
Radecky, Michal [1 ,2 ]
Dvorsky, Marek [1 ,3 ]
Michalek, Libor [1 ,3 ]
Tomis, Martin [1 ,3 ]
机构：
[1] VSB Tech Univ Ostrava, 17 Listopadu 15, Ostrava 70833, Czech Republic
[2] FEECS, Dept Comp Sci, Ostrava, Czech Republic
[3] FEECS, Dept Telecommun, Ostrava, Czech Republic
[4] IT4Innovations, Ctr Excellence, Paris, France
来源：
2015 38TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) | 2015年
关键词：
GSM; prediction; radioclimathology; Symbolic Regression Generic Algorithm;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The impact of weather parameters such as temperature, humidity or dew point on the signal strength in mobile network was investigated. The aim of the paper was to propose a mathematical model which is able to predict the behaviour of such signal strength. The symbolic regression using a genetic algorithm was used to develop a model which predicts the signal strength based on current weather parameters. The average RMSE proved that the model is fully applicable and can be used, for example, in a method of decreasing the power consumption of a base station.
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页数：5
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