Determination of Probability Distribution Function for Modelling Path Loss for Wireless Channels Applications over Micro-Cellular Environments of Ondo State, Southwestern Nigeria
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In this research, the most appropriate probability distribution function for modelling RF signal path loss values in both wet and dry season months over urban, suburban and rural environments of Ondo State are presented. The data used consist of a drive test measurement campaign carried out in a typical urban, suburban and rural areas of Ondo State, South-western Nigeria in both wet and dry season months. The received signal strength (RSS) values were collected and recorded in log files alongside other environmental parameters using TEMS investigation tools. Path loss values were deduced from the measured RSS values. Some selected probability distribution function namely: gamma, lognormal, extreme value, logistic, Weibull and normal distributions function were fitted to the measured path loss values and the best suited one determined using three different metric measures. Results obtained show that normal distribution presents the best probability distribution curve for modelling the RF signal path loss over different micro-cellular environments of Ondo State. A typical result of the rural environment indicates that in wet season months, the normal distribution has RMSE of 7.060 dB, Relative Error of 12.480 % and R2 of 0.988, in dry season months, the RMSE is 9.060 dB, Relative Error of 13.450 % and R2 of 0.985. When compared with other distribution models, the same trend could be seen in other environments, although with different values of RMSE, Relative error and R2. The mean and the standard deviation parameters for the normal distribution estimated, vary seasonal-wise and are environment dependent. However, the rural environment exhibited a wider seasonal variations when compared with the other environments. The results of this research is useful as a first-hand information in the planning of future wireless propagation channels in the studied environments.
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