Path Loss Model Tuning at GSM 900 for a Single Cell Base Station

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Journal Title, Volume, Page: 
Int.J. of Mobile Computing and Multimedia Communications, 5(1), 47-56, January-March 2013
Year of Publication: 
2013
Authors: 
Allam Mousa
Department of Electrical Engineering, An-Najah National University, Nablus, Palestine
Current Affiliation: 
Department Of Electrical Engineering, Faculty Of Engineering, An-Najah National University, Nablus, Palestine
Mahmoud Najjar
Department of Electrical Engineering, An-Najah National University, Nablus, Palestine
Bashar Alsayeh
Department of Electrical Engineering, An-Najah National University, Nablus, Palestine
Preferred Abstract (Original): 
Mobile communications has become an everyday commodity. In the last decades, it has evolved from being an expensive technology for a few selected individuals to today’s ubiquitous systems used by a majority of the world’s population. Imprecise propagation models lead to networks with high co-channel interference, as well as power waste. This study aims to adapt a propagation model in the city of Nablus (Palestine) for a GSM frequency band. This study helps to design better GSM networks for the city in spite of the geographical and frequency limitations. The modification is accomplished by investigating the variation in path loss between the measured and predicted values, according to the propagation model for a specific cell. The results from a simulation model and measured data was compared and analyzed. Bertoni-Walfisch model, without tuning, gave the best results with a mean error of 1.426 dB, which is much less than the mean error obtained by the Standard Macrocell model, 10.91 dB, which is used by a local mobile operator. The two models have been tuned to fit measured data for GSM-900 in the city of Nablus. This is a vital step in cell planning and rollout of wireless networks. To confirm the superiority of Bertoni-Walfisch, a comparison between Bertoni-Walfisch and Standard Macrocell model in terms of Standard Deviation and Mean Error (RMSE).