The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Blind Frequency Offset Estimation Scheme based on ML Criterion for OFDM-based CR Systems in Non-Gaussian Noise

비정규 잡음 환경에서 OFDM 기반 CR 시스템을 위한 ML 기반 블라인드 주파수 옵셋 추정 기법

  • 김준환 (성균관대학교 정보통신공학부) ;
  • 강승구 (성균관대학교 정보통신공학부) ;
  • 백지현 (건국대학교 정보통신공학부) ;
  • 윤석호 (성균관대학교 정보통신공학부)
  • Received : 2011.04.12
  • Accepted : 2011.06.03
  • Published : 2011.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper investigates the frequency offset (PO) estimation scheme for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems. In the CR environments, the conventional FO estimation schemes for the OFDM systems experience significant performance degradation due to the effect of the non-Gaussian noise. In this paper, a novel FO estimation scheme based on the maximum likelihood criterion is proposed for the OFDM-based CR systems in non-Gaussian noise environments. The proposed scheme does not require a specific pilot structure and has a better estimation performance compared with that of the conventional scheme.

본 논문에서는 직교 주파수 분할 다중화 (orthogonal frequency division multiplexing: OFDM) 기반 인지 무선 (cognitive radio: CR) 시스템을 위한 주파수 옵셋 추정 기법에 대해 연구한다. CR 통신 환경에서는 종종 비정규 잡음에 발생하므로 이를 고려하지 않은 주파수 옵셋 추정 기법들의 추정 성능은 크게 하락한다. 본 논문에서는 비정규 잡음 환경에서 OFDM 기반 CR 시스템을 위한 블라인드 방식의 최대 우도 이론 기반 주파수 옵셋 추정 기법을 제안한다. 제안하는 기법은 이제까지의 기법보다 비정규 잡음 환경에서 우수한 추정 성능을 갖는다.

Keywords

References

  1. S. Haykin, "Cognitive radio: brain-empowered wireless communications," IEEE J. Select. Areas Commun., Vol.23, No.2, pp.201-220, Feb., 2005. https://doi.org/10.1109/JSAC.2004.839380
  2. H. Mahmoud, T. Yucek, and H. Arslan, "OFDM for cognitive radio: merits and challenges," IEEE Wireless Commun., Vol.16, No.2, pp.6-15, Apr., 2009.
  3. R. V. Nee and R. Prasad, OFDM for Wireless Multimedia Communications. London, England: Artech House, 2000.
  4. K. Fazel and S. Kaiser, Multi-Carrier and Spread Spectrum Systems. West Sussex, England: John Wiley and Sons, 2003.
  5. T. M. Schmidl and D. C. Cox, "Robust frequency and timing synchronization for OFDM," IEEE Trans. Commun., Vol.45, No.12, pp.1613-1621, Dec., 1997. https://doi.org/10.1109/26.650240
  6. J.-J. van de Beek, M. Sandell, and P. O. Börjesson, "ML estimation of time and frequency offset in OFDM systems," IEEE Trans. Sig. Process., Vol.45, No.7, pp.1800-1805, July 1997. https://doi.org/10.1109/78.599949
  7. F. Moghimi, A. Nasri, and R. Schober, "Lp-norm spectrum sensing for cognitive radio networks impaired by non-Gaussian noise," in Proc. IEEE Global Telecommun. Confer. (Globecom), Honolulu, HI, pp.1-6, Nov., 2009.
  8. K. L. Blackard, T. S. Rappaport, and C. W. Bostian, "Measurements and models of radio frequency impulsive noise for indoor wireless communications," IEEE J. Select. Areas Commun., Vol.11, No.7, pp.991-1001, Sep., 1993. https://doi.org/10.1109/49.233212
  9. M. G. Sanchez, L. de Haro, M. C. Ramon, A. Mansilla, C. M. Ortega, and D. Oliver, "Impulsive noise measurements and characterization in a UHF digital TV channel," IEEE Trans. Electromagn. Compat., Vol.41, No.2, pp. 124-136, May 1999. https://doi.org/10.1109/15.765101
  10. G. Samorodnitsky and M. S. Taqqu, Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance. New York: Chapman & Hall, 1994.
  11. C. L. Nikias and M. Shao, Signal Processing With ${\alpha}$-Stable Distributions and Applications. New York: Wiley, 1995.
  12. T. C. Chuah, B. S. Sharif, and O. R. Hinton, "Nonlinear decorrelator for multiuser detection in non-Gaussian impulsive environments," Electron. Lett., Vol.36, No.10, pp.920-922, May 2000. https://doi.org/10.1049/el:20000656
  13. X. Ma and C. L. Nikias, "Parameter estimation and blind channel identification in impulsive signal environments," IEEE Trans. Sig. Process., Vol.43, No.12, pp.2884-2897, Dec., 1995. https://doi.org/10.1109/78.476432