Statistical Approximations of LOS/NLOS Probability in Urban Environment
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Analysis of line-of-sight and non-line-of-sight (LOS/NLOS) visibility conditions is an important aspect of wireless channel modeling. For statistical channel models the Monte Carlo simulations are usually used to generate spatially consistent visibility states based on particular LOS probability. The present works addresses LOS probability approximation problem using a mix of distance-dependent exponential functions for urban areas with high and low building densities. The proposed model divides site coverage area into LOS and NLOS zones approximated by trigonometric series and support vector classification methods. Compared to commonly used generic ITU-R and 3GPP LOS probability models the proposed approximation is more accurate compared to real world LOS distributions. The accuracy of LOS probability model has been tested against visibility predictions obtained from the digital building data over Manhattan and San Francisco city areas.
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