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Visibility Modeling and Prediction for Free Space Optical Communication Systems for South Africa

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Due to the cost and complexity in the measurement of Free Space Optical (FSO) visibility, this paper presents regression models based on meteorological factors to reliably estimate atmospheric visibility. The meteorological factors used are relative humidity, temperature, fractional sunshine, atmospheric pressure and wind speed for Cape Town, South Africa. Initially, Simple Linear Regression (SLR) models are developed and presented. To improve the performance of the regression, the SLR model is extended to a Multiple Linear Regression model (MLR) where three of the meteorological factors are taken into consideration simultaneously. It was found that by implementing MLR, the model performance improves considerably. However, it was also found that the model had effects of multicollinearity due to some of the predictor variables being highly correlated. To mitigate the effects of multicollinearity, two approaches are proposed, 1) removing the problematic terms from the regression model and 2) introducing interaction terms. Both approaches are seen to have little impact on the overall performance of the MLR model while the estimated model coefficients are significant at 5% significant level. In general, it is found through application of standard statistical tests that both SLR and MLR models can be used adequately to determine visibility at a location.
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Free Space Optics; Visibility; Regression; Correlation Matrix; Multicollinearity; Variance Inflation Factor

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