Title: Geoclimatic Factor K Mapping in Nigeria through Spatial Interpolation

Issue Number: Vol. 8, No. 4
Year of Publication: Dec - 2018
Page Numbers: 253-259
Authors: M.O. Olla, I.B. Oluwafemi
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong
DOI:  http://dx.doi.org/10.17781/P002478

Abstract:


The most important component of all methods for approximating multipath outage probability on terrestrial microwave line-of-sight links (LOS) is the deep fading prediction method. Many of these methods are based on empirical fits of Rayleigh-type distributions to the fading data for individual countries and are characterized in terms of climatic conditions. A universal method for predicting the percentage of time that a certain fade depth is exceeded in the average worst month is provided by the international telecommunication recommendations(ITU-R). The ITU-R method has an additional variable of the geoclimatic factor K in addiction to the link variables. The geoclimatic factor of a region takes into account the variability of climate and terrain. The ITU-Rrecommended that the geoclimatic factor K of a region be got from fading data in the vicinity links of the planned link if such data exist. However, such fading data is not accessible in most cases. Extrapolation methods based on refractivity gradient statistics are recommended for predicting such unavailable data. In this paper, geoclimatic factor K got from radiosonde data for six locations in Nigeria are used to estimate and map the values for all the regions in Nigeria. The Kriging and Inverse Distance Weighting spatial interpolation techniques were used in estimating the geoclimatic factor in places where data is not observable. The performance of these methods were evaluated statistically by calculating the mean absolute error (MAE) and the root mean square error (RMSE) between a set of control points and the interpolated results. The best performing method estimated values is employed to map the seasonal geoclimatic factor K for the entire study region. The estimated values of geoclimatic factor will improve accuracy in predicting multipath outage in LOS links in the region.