Analysis of Artificial Neural Network Model Against Empirical Model (Okumara-Hata Model) For Predicting Pathloss In Gsm Networks
Journal Title: Invention Journal of Research Technology in Engineering & Management - Year 2019, Vol 3, Issue 3
Abstract
Radio propagation prediction is one of the fundamentals of radio network planning. It is thereforevital that the propagation prediction models are as accurate as possible; taking into account the practical limitations that characterized the propagation environment. A drive test was conducted to obtain the field measured data with which the models were appraised. This was done to determine the most suitable model for GSM network deployment in Makurdi, Nigeria. The analysis of the results showed that Okumura – Hata Model, COST 231 – Hata Model, Standard Propagation Model and Stanford University Interim Model gave Root Mean Square Error values of 11.39 dB, 11.59 dB, 8.11 dB and 18.48 dB respectively for GSM900; and 10.75 dB, 9.78 dB, 12.39 dB and 16.99 dB respectively for GSM 1800. Therefore, it was concluded that Standard Propagation Model and COST 231 – Hata Model would be more suitable for GSM 900 and GSM 1800 network planning and deployment respectively in Umuahia City,
Authors and Affiliations
Umesi Cosmos
Keywords
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