hus signals are in a frequency flat environ- rameters bi and Cjk, for p = 10%, are shown in Table 4.7-9. ment. For large values of Box, the fading depth decreases Values for different values of p can be found in [CaCo01] for increasing system bandwidths. and [Card04]. A different approach, which is based on environment Since there is a close relation between the physical and properties, more precisely on the differences in propa- geometrical environment characteristics and the PDP of gation path length among different arriving components, the propagation channel (hence, the RMS delay spread), is presented in [CaCo01]. The proposed approach, ac- a simple relationship between the maximum difference in counting for the maximum difference in propagation propagation path length among different arriving compo- path length, Almax, and having also the Rice factor as nents and the RMS delay spread of the propagation a parameter, allows evaluating the fading depth, mea- channel can be established, therefore bridging the gap sured betweenp and 50% of the received power CDF, between the two previous models [CaCo03] from a simple mathematical expression Almax card (4.7.21) FD,(K,BAlmax/(8BI where C is the speed of light. Sp(K), Table 4.7-9 Parameters bi and Cjk for = 10%. Sp(K) 8.080 0.289 0.141 0.452 (4.7.16) 0.070 0.225 0.338 0.180 where Sp(K), A1,p(K), A2,p(K) and A3,p(K) are mathe- 0.690 0.349 2.650 0.689 matical functions of K that depend on p, and Wb,p is a breakpoint value depending also on p. -0.410 0.421 0.610 2.295 2.943 CHAPTER 4.7 Propagation modelling and channel characterisation This allows one to use any of the proposed approaches In the literature on measurements and modelling of for evaluating the fading depth in a given environment, time-variant radio channels, there has almost always been defined either by physical and geometrical properties or a confinement to moving transmitters or receivers in by the PDP. This approach, being simple, is effective for a static environment. For applications of practical in