Mobile communications design fundamentals (Wiley Series in by William C. Y. Lee

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By William C. Y. Lee

Revised and enlarged model that discusses tips on how to layout a cellular communications process. Comprehensively examines the cellular radio setting. Covers prediction of propagation loss, calculation and strategies of lowering fades, interference, frequency plans and linked schemes, layout parameters, signaling and channel entry, mobile CDMA, microcell structures, and miscellaneous similar platforms. includes chapter-by-chapter references and difficulties.

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27) shows that the product of two second-order statistical functions become a first-order statistical function. 5 Correlation and Power Spectrum Correlations There are two kinds of correlations, autocorrelation and crosscorrelation. Their general expressions are as follows: Autocorrelation Functions. Let two random variables χλ and x2 be two random processes, x(ti) and x(tx + τ), respectively. *i = x(h) x2 = x(t2) = x(tx + T) An autocorrelation function is obtained from an ensemble average of the product of xx and x2.

In presenting a fading signal, A¿ is a complex random variable with zero mean and variance 1, and 0, is also a random'variable from 0° to 360°. 15) represents a fading signal. Amplifying the picture shown in Fig. 5E, and adding many pairs of standing waves (each one is the same as shown in 16 THE MOBILE RADIO ENVIRONMENT case 4), the maximum fading frequency can be obtained from Eq. 16) which is the same as the maximum Doppler frequency fD shown in Eq. 9). 3 Classification of Channels3 In a dispersive medium, there are two kinds of spread: Doppler spread F and multipath spread δ.

We will describe these topics in later chapters. 1 Averages In real data processing there are sample averages x(t) and biased time averages x(t). In statistics there are ensemble averages E[x] and unbiased time averages < * ( ' ) > ■ Sample Average (x) The samples are averaged as a conventional arithmetical average N Σ xi DEFINITIONS OF NECESSARY TERMS AND THEIR APPLICATIONS 21 . 7. Illustration of sample averages. where x, is a random variable. N should be large in order to claim x as a meaningful average.

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