A quantitative evaluation of generation methods for correlated Rayleigh random variates

A number of different algorithms are used for the generation of correlated Rayleigh random variates. However, evaluations of and comparisons between various variate generation methods using meaningful quantitative measures are believed to be lacking. Previously, new quantitative quality measures for random variate generation have been proposed that are, in particular, meaningful and useful for digital communication system simulation. This paper presents the application of these measures to four methods of correlated variate generation, comparing the algorithms in terms of the quality of the generated samples and the required computational effort. The four methods are the IDFT method, filtering of white Gaussian noise (WGN), filtering of WGN using a third-order Butterworth filter, and the Monte-Carlo superposition of sinusoids method