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

  • 제38C권4호
  • /
  • Pages.365-370
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  • 2013
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  • 1226-4717(pISSN)
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  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지
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비정규 잡음에 강인한 ML기반 OFDM 블라인드 주파수 옵셋 추정기

ML-Based and Blind Frequency Offset Estimators Robust to Non-Gaussian Noise in OFDM Systems

  • 심정윤 (성균관대학교 정보통신대학) ;
  • 윤석호 (성균관대학교 정보통신대학) ;
  • 김광순 (연세대학교 전기전자공학부) ;
  • 이성로 (목포대학교 정보전자공학과)
  • 투고 : 2013.01.14
  • 심사 : 2013.03.08
  • 발행 : 2013.04.30
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초록

본 논문에서는 비정규 잡음에 강인한 직교 주파수 분할 다중화 (orthogonal frequency division multiplexing: OFDM) 블라인드 주파수 옵셋 추정기들을 제안한다. 먼저 복소 등방성 코시 과정으로 모델링 된 비정규 잡음 환경에서 최대 우도 (maximum likelihood: ML) 추정기를 제안한다. 또한, ML 기반의 보다 간단한 추정기를 제안한다. 모의실험을 통해 제안한 추정기들이 비정규 잡음에 강인하며 기존 추정기보다 우수한 주파수 옵셋 추정 성능을 가짐을 보인다.

In this paper, we propose robust blind estimators for the frequency offset of orthogonal frequency division multiplexing in non-Gaussian noise environments. We first propose a maximum likelihood (ML) estimator in non-Gaussian noise modeled as a complex isotropic Cauchy process, and then, a simpler estimator based on the ML estimator is proposed. From numerical results, we confirm that the proposed estimators are robust to the non-Gaussian noise and have a better estimation performance over the conventional estimator in non-Gaussian noise environments.

키워드

참고문헌

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