Autocorrelation-Based Quickest Change Detection

Afser H., Yabaci S. B.

IEEE COMMUNICATIONS LETTERS, cilt.24, sa.12, ss.2913-2916, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 12
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/lcomm.2020.3016652
  • Dergi Adı: IEEE COMMUNICATIONS LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2913-2916
  • Çukurova Üniversitesi Adresli: Evet

Özet

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.