1 research outputs found

    Optimization of CCIR Pathloss Model Using Terrain Roughness Parameter

    Get PDF
    In this paper, optimizing CCIR  pathloss model  using terrain roughness parameter is presented. The study is based on field measurement of received signal strength and elevation profile data obtained in a suburban area of Uyo for   800 MHz GSM network. Particularly,  in this paper, the mean elevation and the standard deviation of elevation are used separately to minimize the error using least square method.  The results show that the untuned CCIR  model has a RMSE of  28.8 dB and prediction accuracy of 77.4 %. On the other hand, both the pathloss predicted by the mean elevation tuned CCIR  model and the pathloss predicted by the standard deviation of elevation tuned CCIR  model have  the same RME of 3.9 dB and prediction accuracy of 97.6 %. The terrain roughness correction factors are the same value (that is, C_M ̅ = C_Š=  28.50882771). The RMSE of 3.9dB shows  that the terrain roughness parameter-based  tuning  approach can effectively be used to minimize the prediction error of the CCIR  model within the acceptable value  which is about 7dB to 10 dB for suburban and rural areas
    corecore