Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Blind Algorithms using a Random-Symbol Set under Biased Impulsive Noise

바이어스 된 충격성 잡음 하에서 랜덤 심볼 열을 이용한 블라인드 알고리듬

  • Kim, Namyong (School of Electronic, Info. & Comm. Engineering, Kangwon National University)
  • 김남용 (강원대학교 전자정보통신공학부)
  • Received : 2012.10.16
  • Accepted : 2013.04.11
  • Published : 2013.04.30
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Abstract

Distribution-matching type algorithms based on a set of symbols generated in random order provide a limited performance under biased impulsive noise since the performance criterion for the algorithms has no variables for biased signal. For the immunity against biased impulsive noise, we propose, in this paper, a modified performance criterion and derived related blind algorithms based on augmented filter structures and the distribution-matching method using a set of random symbols. From the simulation results, the proposed algorithm based on the proposed criterion yielded superior convergence performance undisturbed by the strong biased impulsive noise.

랜덤 순서로 발생된 심볼 열을 기반으로 하는 확률 분포 매칭 타입의 알고리듬들은 그 성능 기준이 바이어스된 신호에 대한 변수를 지니고 있지 않아서 바이어스된 충격성 잡음 하에서는 제한된 성능을 나타낸다. 이 논문에서는 바이어스된 충격성 잡음을 이겨내기 위한 수정된 성능기준을 제안하고, 증강된 필터구조와 랜덤 심볼 열을 사용하는 확률 분포 매칭 방법에 기초한 블라인드 알고리듬을 제안하였다. 시뮬레이션 결과로부터 제안된 성능기준에 의해 만들어진 제안된 알고리듬이 바이어스된 강한 충격성 잡음에 대해 동요됨이 없이 탁월한 수렴성능을 보였다.

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