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

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

  • 김준환 (성균관대학교 정보통신공학부) ;
  • 강승구 (성균관대학교 정보통신공학부) ;
  • 백지현 (건국대학교 정보통신공학부) ;
  • 윤석호 (성균관대학교 정보통신공학부)
  • 투고 : 2011.04.12
  • 심사 : 2011.06.03
  • 발행 : 2011.06.30

초록

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.

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.

키워드

참고문헌

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