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Signal Received Power Mapping in Wireless Communication Networks using Time Series and Geostatistics

Journal: International Journal of Advanced Engineering Research and Science (Vol.8, No. 10)

Publication Date:

Authors : ;

Page : 035-050

Keywords : ARIMA Model; Geostatistics; Kriging; Multivariate Temporal Modeling; Wireless.;

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Some theoretical and experimental models have been considered for the prediction of the path loss in mobile communications systems. However, one knows that in real environment, the received signal is subject to variations. The model developed for an urban area cannot give resulted acceptable for different urban areas since that, each model has different parameters in accordance with the considered area. This paper presents the results of propagation channel modeling, based on multivariate time series models using data collected in measurement campaigns and the main characteristics of urbanization in the city of Belem-PA. Transfer function models were used to evaluate effects on the time series of received signal strength (dBm) which was used as the response variable and as explanatory variables of the height of buildings and distances between buildings. As time series models disregard to the possible correlations between neighboring samples, we used a geostatistical model to establish the correctness of this model error. The results obtained with the proposed model showed a good performance compared to the measured signal, considering the data of the eleven routes from the center of the city of Belém/Pa. From the map of the spatial distribution of the received signal strength (dBm), one can easily identify areas below or above dimensional in terms of this variable, that is benefited or damaged compared with the signal reception, which may result in a greater investment of the local operator (concessionaire mobile phone) in those regions where the signal is weak.

Last modified: 2021-10-30 14:57:28