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resolution of the UWB system is 15 times lower and many more paths are measured with the UWB system An increase in the number of paths does not change the total power and rms delay spread of the channel but has an impact on the arrival rate and the statistics of uctuations on the paths In general, one can assume that for ultrabandwidth, all paths are isolated and the amplitude of each path is xed As the terminal is moved or people move about in the space between the transmitter and receiver, the amplitudes of the paths change due to shadow fading, which as we discussed in Section 42, exhibits a lognormal distribution As the bandwidth becomes narrower, neighboring paths combine their amplitudes and phases, much as in Fig 33.





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This results in rapid uctuation of the composite signal amplitude as a result of the rapid phase changes in each path, producing fast multipath or Rayleigh fading One of the main physical characteristics of UWB transmission is the stability of the received signal This stability, which is due to its ultrawideband characteristics, isolates the paths, avoids the multipath Rayleigh fading, and exhibits only lognormal shadow fading This observation leads to the conclusion that existing channel models, such as Saleh Valenzuela s model, described in Section 622, which assumes that individual paths are Rayleigh distributed, are not valid for UWB channel modeling and need to be modi ed In the following paragraphs we describe the latest modi cation to the Saleh Valenzuela model considered by the IEEE 80215 WPAN community.

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This modi ed model is based on measurements performed at Intel [Foe02] and is also referred to as Intel s model During the standardization activities in the IEEE 80215 committee, the IEEE 80211 model, Saleh Valenzuela s model (Section 622), and the modi ed Poisson or K model (Section 623) were examined with the same set of data, and it was found that Intel s model best t the measured data reported in [Foe02] Intel s Model for UWB Multipath Propagation This model begins with the framework of the double-cluster Saleh Valenzuela channel impulse response given in Eq (6210), changes the statistical model for the amplitude kl and phase kl , and adjusts the arrival rates of the clusters and paths within the clusters.

The amplitude of the signal, kl , is assumed to be lognormal, and the phase, kl , is modeled as a binary number taking only two values, 0 and 180 , with equal probability To form the lognormal distribution, it is assumed that 20 log10 kl has a normal distribution function with mean and variance of kl and 2 , respectively To show that the lognormal is the best t for the amplitudes, a curve- tting process similar to Fig 4131 was applied to the measured data The mean of the lognormal distribution is given by kl = 10 ln( 2 (0, 0) 10Tl / ln(10) 10 k,l / 2 ln(10) 20.

(2.A.4)

Using this equation we only need to know the extant number of lineages (Nd) and the total time period over which they have been in existence (d) to estimate the diversi cation rate Later we will consider how to describe these processes in continuous time The branching patterns of real clades are far more complex than that given in Fig 27 Phylogenetic trees (phylogenies) which describe the relationship between different extant or fossil groups have been determined for many clades (some examples are given in Fig 28) Phylogenies are constructed by comparing the character sets of different organisms and determining their similarity Guiding principles of phylogenetic (re)construction include parsimony, which produces a hypothesis of the simplest way of arranging the organisms by minimizing the number of transitions between character states.

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