Abstract
The paper addresses the applicability of Okumura-Hata model in an area in Oman in GSM frequency band of 890-960 MHz. The Root Mean Square Error (RMSE) was calculated between measured Pathloss values and those predicated on the basis of Okumura-Hata model. We proposed the modification of model by investigating the variation in Pathloss between the measured and predicted values. This modification is necessary to consider the environmental conditions of OMAN. Artificial Neural Network (ANN) was also used to forecast the data for much larger distance. ANN provides a wide and rich class of reliable and powerful statistical tools to mimic complex nonlinear functional relationships. Here, feed forward Multilayer Perceptron (MLP) network was used. A typical MLP network consists of three layers i.e. input layer, hidden layer and output layer. The trained neural nets are finally used to make desired forecasts. These results are acceptable and can be used for OMAN.
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Nadir, Z., Ahmad, M.I. (2014). RF Coverage and Pathloss Forecast Using Neural Network. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_36
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DOI: https://doi.org/10.1007/978-3-319-01857-7_36
Publisher Name: Springer, Cham
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