Identification of OFDM Signals using Cyclic Autocorrelation Function


TEKBIYIK K., ALAKOCA H. , TUGREL H. B. , AYYILDIZ C., Kurt G. Z.

National Conference on Electrical, Electronics and Biomedical Engineering (ELECO), Bursa, Turkey, 1 - 03 December 2016, pp.622-626 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Bursa
  • Country: Turkey
  • Page Numbers: pp.622-626

Abstract

Diversifying and developing wireless communication technologies give rise to many problems. Two of the main problems are efficient usage of frequency spectrum and security. The techniques that are used to solve such problems strictly need detection of signal types. When unwanted symbols are detected, these signal sources can be stopped or their interfering components can be canceled from the information bearing signal. In this paper, the problem of identifying cyclic prefixed-orthogonal frequency division multiplexing (OFDM) signals is considered by using a (cyclic autocorrelation function, CAF) based approach. Via simulation results, it is shown that with the proposed approach, the signals can be distinguished from each other according to their cyclic prefix lengths.