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11.1.1. Statistical Distribution of Buildings in Urban Environments In 5, by introducing the stochastic approach, we have assumed that the number of rays N, which arrive at the receiver during time t after multiple diffuse re ections by randomly distributed buildings lining the streets or on the terrain, can be described by the Poisson distribution described in 5 (see also References [14 21]). An array of buildings (nontransparent scatterers) was presented there as an ordinary and simple ow of positive virtual pulses, where each pulse represents the real building location at the terrain. Such mathematical description of an array of buildings randomly distributed around both terminal antennas allowed us, in 5, to determine a probability of direct visibility between antennas and other statistical functions. Finally, we used them to derive the average eld intensity as a superposition of coherent and incoherent components of the total signal average intensity. Poisson s law strictly describes the real situation of building distribution in the urban environment with randomly distributed buildings as nontransparent screens. To verify this law for real situations in the urban scene, statistical analysis of topographic maps of built-up areas that correspond to the experimental sites mentioned in References [15 28] was carried out. This procedure was based on the following algorithm. If the randomly distributed buildings create a ow of randomly distributed positive virtual pulses placed at the smooth plane, then the distribution of such pulses of amount m, at the limit segment d, along the radio path must be described according to Poisson s law by the following probability function Pd m m m expf mg m! 11:1

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where the mean number of positive virtual pulses, m, within the segment d can be presented in the following form [14,21]:

l 0

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116 117 118 119 122

11:2

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As de ned in 5, r1 is the projection of the vector to the transmitter at the ground plane z 0 (see Fig. 5.15, 5); q r2 r1 =d is a unit vector at the ground plane z 0; d jr2 r1 j, where r2 is the projection of the vector to the receiver at the ground plane z 0; parameter g0 determines the density of the building contours at the plane z 0 and was de ned by (5.59) in 5. To obtain the real form of probability function Pd m , we must use the following computational procedure based on the statistical analysis of topographic maps from the tested built-up areas and compare it with Poisson s distribution (11.1). We have analyzed topographic maps of experimental sites where continuous measurements have been carried out, for example, in Stockholm (Sweden), Arhus, Aalborg, and Copenhagen (Denmark), Lisbon (Portugal), Helsinki (Finland), Jerusalem, Ramat-Gan, Beer-Sheva, and Tel-Aviv (Israel). We have used only similar areas

FIGURE 11.1. The building distribution above shows the terrain for each tested radio path: 200 m, 500 m and 800 m, respectively. Continuous curves describe statistical data; dashed curves describe the actual Poisson distributions according to eqn. (11.1).

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