Abstract

In this paper, RMSE and functional composition of residual are used as correction factors for tuning Hata model in the suburban area and 800-900MHz GSM frequency band. The study is based on empirical measurements conducted at Abak town, a suburban area in Akwa Ibom state, Nigeria. The tuned model is obtained by adding the correction factor to the original Hata pathloss model for the suburban area. The results showed that the functional composition of residual - based tuning approach has better prediction performance when compared with the RMSE-based tuning approach. Particularly, when the functional composition tuning approach is employed Hata model has the lowest RMSE value of 4.47, the highest prediction accuracy of 97.19% and the highest competitive success rate of 64.29%. On the other hand, the RMSE-tuned Hata model has a higher RMSE value of 7.03, lower prediction accuracy of 96.19% and the lower competitive success rate of 35.71%.

Highlights

  • Accurate prediction of pathloss is very essential in GSM network planning and optimization

  • The functional composition of the residual is generated by fitting nonlinear equation, E (d) to the graph of e (d) versus P{(d)as shown in Table 2 and figure 1 where E (d) is given as; E(d) =

  • The study is based on empirical measurements conducted at Abak town, a suburban area in Akwa Ibom state, Nigeria

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Summary

Introduction

Accurate prediction of pathloss is very essential in GSM network planning and optimization. Pathloss is the reduction in power density of an electromagnetic wave signal at it propagates from the transmitter to the receiver [1]. Propagation pathloss models are used to calculate pathloss during transmission of a signal so as to predict the mean signal strength for an arbitrary transmitter-receiver separation distance [2,3,4,5]. The empirical models are frequently used for outdoor pathloss predictions. In practice, empirical pathloss model tuning is usually required due to significant drop in prediction performance of empirical models when applied in the environments other than the ones they are designed

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