 mean azimuth and elevation (4.7.15) AOA of 45° and 90°, respectively, and an elevation spread of 0°, as a function of azimuth spread, are presented in Figure 4.7-36. Propagation modelling and channel characterisation CHAPTER 4.7 where ad is the magnitude of the LoS component, K is the Rice factor, IO is the Bessel function of first kind and K=0dB K=6dB zeroth order, and am are eigenvalues of a covariance K=9dB matrix obtained, by generating a matrix whose elements K=12dB are given by the product between the correlation func- tion between different frequency components, the fre- quency response of the filter used in the transmitting equipment, and an incremental bandwidth that depends on the system bandwidth. 0.001 When K tends to zero the Rice distribution associated B.O. (Hz.s) to the first path degenerates to the Rayleigh one, there- fore corresponding to the NLoS case. Figure 4.7-37 Fading depth, exponential model [CaCo02]. By using this model, the fading depth for different For any given value of p, functions Sp(K), A1,p(K), channel models can be easily evaluated for different A2,p(K) and A3,p(K) can be evaluated from PDPs. When represented as a function of the Rice factor, and of the product between the system bandwidth and (4.7.17) the RMS delay spread of the propagation channel, one gets a graph like the one in Figure 4.7-37. The results in Figure 4.7-37 correspond to the case of a continuous exponential decaying function with decay A1[dB] C14 (4.7.18) rate equal to the inverse of the RMS delay spread, thus being representative of a large set of channel models, commonly used for simulating the propagation channel. As one can observe, for each value of K, the fading depth remains practically constant for Bo < 0.02 Hzs. This A3 = C34 (4.7.20) corresponds to a situation where the system bandwidth is below the coherence bandwidth of the propagation where parameters bi(i=1,...,5) and Cjk (j=1, = channel, defined for a frequency correlation of 90% ..., 4) depend on the value of p. Values for the pa- [Rapp86], t