Mean-Square Consistent Estimation of the Spectral Correlation Density for Spectrally Correlated Stochastic Processes

In this paper, the problem of estimating the spectral correlation density of spectrally correlated stochastic processes is addressed. These processes have Loeve bifrequency spectrum with spectral masses concentrated on a countable set of support curves in the bifrequency plane. The almost-cyclostationary processes are obtained as a special case when the support curves are lines with unit slope. Spectrally correlated processes find application in wide-band or ultrawideband mobile communications. It is shown that the cross-periodogram frequency smoothed along a known support curve and properly normalized provides a mean-square consistent estimator of the spectral correlation density of the Loeve bifrequency spectrum along that curve.