RF coverage and pathloss forecast using neural network

Zia Nadir*, Muhammad Idrees Ahmad

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

4 اقتباسات (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.

اللغة الأصليةEnglish
عنوان منشور المضيفAdvances in Systems Science - Proceedings of the International Conference on Systems Science, ICSS 2013
المحررونJerzy Świątek, Adam Grzech, Paweł Świątek, Jakub M. Tomczak, Jerzy Świątek
ناشرSpringer Verlag
عدد الصفحات10
رقم المعيار الدولي للكتب (الإلكتروني)9783319018560
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2014
الحدثInternational Conference on Systems Science, ICSS 2013 - Wroclaw, Poland
المدة: سبتمبر ١٠ ٢٠١٣سبتمبر ١٢ ٢٠١٣

سلسلة المنشورات

الاسمAdvances in Intelligent Systems and Computing
مستوى الصوت240
رقم المعيار الدولي للدوريات (المطبوع)2194-5357


OtherInternational Conference on Systems Science, ICSS 2013

ASJC Scopus subject areas

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