Autocorrelation-Based Quickest Change Detection


Afser H., Yabaci S. B.

IEEE COMMUNICATIONS LETTERS, vol.24, no.12, pp.2913-2916, 2020 (SCI-Expanded, Scopus)

  • Publication Type: Article / Article
  • Volume: 24 Issue: 12
  • Publication Date: 2020
  • Doi Number: 10.1109/lcomm.2020.3016652
  • Journal Name: IEEE COMMUNICATIONS LETTERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.2913-2916
  • Çukurova University Affiliated: Yes

Abstract

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.