RF coverage and pathloss forecast using neural network

Zia Nadir*, Muhammad Idrees Ahmad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationAdvances in Systems Science - Proceedings of the International Conference on Systems Science, ICSS 2013
EditorsJerzy Świątek, Adam Grzech, Paweł Świątek, Jakub M. Tomczak, Jerzy Świątek
PublisherSpringer Verlag
Number of pages10
ISBN (Electronic)9783319018560
Publication statusPublished - 2014
EventInternational Conference on Systems Science, ICSS 2013 - Wroclaw, Poland
Duration: Sept 10 2013Sept 12 2013

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


OtherInternational Conference on Systems Science, ICSS 2013


  • Artificial neural network
  • Hata model
  • Pathloss model
  • Propagation models
  • Semi-urban area

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science


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