On multivariate Rayleigh and exponential distributions

TLDR: Expressions for multivariate Rayleigh and exponential probability density functions (PDFs) generated from correlated Gaussian random variables can serve as a useful tool in the performance analysis of digital modulation over correlated Rayleigh-fading channels using diversity combining.

Abstract: In this paper, expressions for multivariate Rayleigh and exponential probability density functions (PDFs) generated from correlated Gaussian random variables are presented. We first obtain a general integral form of the PDFs, and then study the case when the complex Gaussian generating vector is circular. We consider two specific circular cases: the exchangeable case when the variates are evenly correlated, and the exponentially correlated case. Expressions for the multivariate PDF in these cases are obtained in integral form as well as in the form of a series of products of univariate PDFs. We also derive a general expression for the multivariate exponential characteristic function (CF) in terms of determinants. In the exchangeable and exponentially correlated cases, CF expressions are obtained in the form of a series of products of univariate gamma CFs. The CF of the sum of exponential variates in these cases is obtained in closed form. Finally, the bivariate case is presented mentioning its main features. While the integral forms of the multivariate PDFs provide a general analytical framework, the series and determinant expressions for the exponential CFs and the series expressions for the PDFs can serve as a useful tool in the performance analysis of digital modulation over correlated Rayleigh-fading channels using diversity combining.