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거친 오차 추정과 미세 오차 추정을 활용한 블라인드 적응 알고리즘

Blind Adaptation Algorithms Using Coarse Error Estimation and Fine Error Estimation

  • 오길남 (광주대학교 광통신공학과)
  • Oh, Kil-Nam (Dept. of Optical Communications Engineering, Gwangju University)
  • 투고 : 2012.06.11
  • 심사 : 2012.08.09
  • 발행 : 2012.08.31

초록

블라인드 등화에서 등화 초기에는 눈모형을 빠르게 여는 것이 필요하고, 이후에는 등화기 출력 신호의 오차 레벨을 낮추는 것이 중요하다. 본 논문에서는 특별하게 정해지는 신호점을 사용한 거친 오차 추정과 원 신호점을 사용한 미세 오차 추정을 동시에 산출하고, 두 오차 추정을 활용하는 방식을 제안한다. 두 오차 추정은 각각 눈모형이 닫힌 상태에서 눈모형을 빠르게 열거나, 눈모형이 열리기 시작한 이후 정상상태에서 오차 레벨을 낮추는데 효과적이다. 등화기의 수렴 상태에 따라 두 오차 추정 중 하나를 선택하거나, 두 오차 추정의 상대적 신뢰도에 따라 두 오차를 가중 결합하여 새로운 오차를 산출하는 두 블라인드 등화 알고리즘을 제안하고 그 성능을 비교한다.

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.

키워드

참고문헌

  1. D. Ashmawy, K. Banovic, E. Abdel-Raheem, M. Youssif, H. Mansour, and M. Mohanna, "Joint MCMA and DD blind equalization algorithm with variable-step size," in Proc. IEEE Int. Conf. Electro/Information Technology, pp. 174-177, 2009.
  2. C.A.R. Fernandes, G. Favier, and J.C.M. Mota, "Decision directed adaptive blind equalization based on the constant modulus algorithm," Signal, Image and Video Processing, vol. 1, no. 4, pp. 333-346, 2007. https://doi.org/10.1007/s11760-007-0027-2
  3. W. Rao, "New concurrent modulus algorithm and soft decision directed scheme for blind equalization," Procedia Environmental Sciences 10, pp. 1264-1269, 2011. https://doi.org/10.1016/j.proenv.2011.09.202
  4. S. Abrar, "A family of reduced-constellation algorithms for blind equalization of square-QAM Signals," ICM 2005, pp. 296-300, Dec. 2005.
  5. D.N. Godard, "Self-recovering equalization and carrier tracking in two-dimensional data communication systems," IEEE Trans. Commun., vol. COM-28, pp. 1867-1875, Nov. 1980.
  6. J.R. Treichler and B.G. Agee, "A new approach to multipath correction of constant modulus signals," IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, pp. 459-472, Apr. 1983.
  7. K.N. Oh, "Single/multilevel modulus algorithm for blind equalization of QAM signals," IEICE Trans. Fundamentals of Electronics, Communications and Computer Sciences, vol. E80-A, no. 6, pp. 1033-1039, June 1997.
  8. G. Picchi and G. Prati, "Blind equalization and carrier recovery using a "Stop-and-Go" decisiondirected algorithm," IEEE Trans. Commun., vol. COM-35, no. 9, pp. 877-887, Sep. 1987.