Autocorrelation-Based Quickest Change Detection

We consider the utilization of the autocorrelation information for aiding the quickest detection problem. Specifically, we investigate the problem of quickly detecting a Gaussian source with autocorrelation such that some of its symbols are repeated as cyclic prefixes. Based on the cumulative sum algorithm, we propose a method which takes advantage of this autocorrelation in order to provide performance improvement compared to the classical energy based detection of the uncorrelated source.