ualization for inter- ference cancellation in spread spectrum multiple access systems," IEEE 42d Trans. Veh. Tech. Conf., pp. 71-74, 1992. [40] M. Abdulrahman, A. U. H. Sheikh, and D. D. Falconer, "DFE convergence for interference cancellation in spread spectrum multiple access systems," IEEE 43d Trans. Veh. Tech. Conf., pp. 807-810, 1993. [41] A. J. Viterbi, Principles of Spread Spectrum Multiple Access Communication, Englewood Cliffs, NJ: Prentice-Hall, in press. APPENDIX 3A. MULTIPATH AND DIVERSITY In this appendix, we investigate the Rayleigh fading channel model and the use of diversity techniques to overcome some of the deep fade problems typ- ically encountered in these radio channels. Rayleigh Fading Model The biggest limitation to mobile radio peformance is propagation impair- ment owing to multipath. Typically, a continuous wave (CW) channel input signal of the form A cos WOT (3A.1) where A is a constant has at the output of a multipath channel a signal of the form R cos(wft + o) (3A.2) where R is a random amplitude variable and is a random phase variable. The phase term is almost always accurately modeled as having a uniform probability density over all phases. The mathematical model for the random amplitude variable is less cer- tain, and the results are very sensitive to this model. As illustrated in Figure 3A.1, the most common assumption is that in-phase and quadrature com- ponents of the signal experience several independent amplitudes SO that the sum of the independent in-phase amplitude terms contributing to amplitude is given by the random variable X, while the corresponding quadrature term is another independent random variable Y. The Central Limit Theorem states that if the number of independent random multipath reflections is large, X and Y can be modeled as independent Gaussian random variables. It is important to note that the accuracy of this Gaussian approximation is highest near the mean values of these random variables and declines as the approximation departs from mean values. The amp