Abstract
Clutter loss in the presence of built (urban and suburban) environments significantly depend on whether an unobstructed line-of-sight (LOS) path exists (or does not) between the two endpoints: a base station located at elevation and a client/user equipment at ground level. The objective of this article is to develop a new computationally efficient statistical approach to estimating the probability of LOS versus non-LOS (NLOS) paths for a region of interest. The initial development used a spatial 1-D Poisson process model for built environments that captured two key parameters: 1) the average spatial density and 2) the height distribution of buildings. Thereafter, natural terrain variations was included on top of the built environment to develop a more generalized and accurate 2-D model for discrimination. The final model is driven by input parameters obtained from actual data from different regions, to assess their effectiveness on resulting LOS/NLOS discrimination in real-world scenarios.
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