Skip to main navigation Skip to search Skip to main content

Reliable blind channel estimation scheme based on cross-correlated cyclic prefix for OFDM system

Kim Taejoon, Eo Iksoo

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

This paper proposes an efficient and reliable blind channel estimation method for single transmitter and receiver antenna orthogonal frequency division multiplexing (OFDM) system. The proposed blind channel estimation method is based on the interesting cross-correlation property of the repeated structure of cyclic prefix (CP) in an OFDM symbol. Our cross-correlation based method, which utilizes the only information in CP, not entire symbol, is robust to additive white noise and not affected from the presence of null channel coefficients. Toeplitz structure induced in the cross-correlation matrix allows us a simple and reliable method for extracting channel impulse response effectively. In the simulation study, proposed method is compared with auto-correlation based approach and it demonstrate the superior performance of the proposed method.
Original languageEnglish
Title of host publication8th International Conference Advanced Communication Technology, ICACT 2006 - Proceedings
Pages3-5
Volume1
Publication statusPublished - 2006
Externally publishedYes
Event8th International Conference Advanced Communication Technology (ICACT 2006) - Phoenix Park, Korea, Republic of
Duration: 20 Feb 200622 Feb 2006

Publication series

Name
Volume1

Conference

Conference8th International Conference Advanced Communication Technology (ICACT 2006)
Abbreviated titleICACT2006
PlaceKorea, Republic of
CityPhoenix Park
Period20/02/0622/02/06

Research Keywords

  • Blind channel estimation
  • Cross correlation
  • OFDM system
  • SVD
  • Toeplitz matix

Fingerprint

Dive into the research topics of 'Reliable blind channel estimation scheme based on cross-correlated cyclic prefix for OFDM system'. Together they form a unique fingerprint.

Cite this