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Self-Adaptive Performance Improvement of Novel SDD Equalization Using Sigmoid Estimate and Threshold Decision-Weighted Error

시그모이드 추정과 임계 판정 가중 오차를 사용한 새로운 SDD 등화의 자기적응 성능 개선

  • Oh, Kil Nam (Dept. of Healthcare & Medical Engineering, Gwangju University)
  • 오길남 (광주대학교 보건의료공학과)
  • Received : 2016.05.31
  • Accepted : 2016.08.11
  • Published : 2016.08.31

Abstract

For the self-adaptive equalization of higher-order QAM systems, this paper proposes a new soft decision-directed (SDD) algorithm that opens the eye patterns quickly as well as significantly reducing the error level in the steady-state when it is applied to the initial equalization stage with completely closed eye patterns. The proposed method for M-QAM application minimized the computational complexity of the existing SDD by the symbol estimated based on the two symbols closest to the observation, and greatly simplified the soft decision independently of the QAM order. Furthermore, in the symbol estimating it increased the reliability of the estimates by applying the superior properties of the sigmoid function and avoiding the erroneous estimation of the threshold function. In addition, the initialization performance was improved when an error is generated to update the equalizer, weighting the symbol decision by the threshold function to the error, resulting in an extension of the range of error fluctuations. As a result, the proposed method improves remarkably the computational complexity and the properties of initialization and convergence of the traditional SDD. Through simulations for 64-QAM and 256-QAM under multipath channel conditions with additive noise, the usefulness of the proposed methods was confirmed by comparing the performance of the proposed 2-SDD and two forms of weighted 2-SDD with CMA.

고차 QAM 시스템에 대한 자기적응 등화에서 눈 모형이 완전히 닫힌 등화 초기에 적용하여 눈 모형을 빠르게 열뿐만 아니라 정상상태 오차 레벨을 크게 낮추는 새로운 SDD 알고리즘을 제안한다. 제안 방법은 M-QAM 응용에서, 관찰에 가장 인접한 두 심볼을 추정의 기반으로 함으로써 기존 SDD의 계산 복잡성을 최소화하고, QAM 차수에 무관하게 연판정을 크게 단순화하였다. 아울러 심볼 추정에 임계 함수에 비해 오판정 회피가 우수한 시그모이드 함수를 적용, 추정의 신뢰도를 높였다. 또한 등화기 갱신을 위한 오차 발생 시 임계 함수에 의한 심볼 판정 값을 오차에 가중하여 오차 변동 범위를 확장함으로써 제안한 자기적응 등화기의 초기화 성능을 개선하였다. 결과적으로 제안 방법은 기존 SDD의 계산 복잡성과 초기화 및 수렴 특성을 현저히 개선하였다. 부가 잡음이 존재하는 다중경로 채널 조건에서 64-QAM 및 256-QAM에 대한 모의실험을 통해 CMA와 제안한 2-SDD 및 가중된 2-SDD의 두 가지 형태의 성능을 비교하고 제안 방법의 유용성을 확인하였다.

Keywords

References

  1. O. Macchi, E. Eweda, "Convergence analysis of self-adaptive equalizers," IEEE Trans. Information Theory, vol. 30, no. 2, pp. 161-176, Mar. 1984. DOI: http://dx.doi.org/10.1109/TIT.1984.1056896
  2. S. Abrar, A. Zerguine and A.K. Nandi, "Adaptive blind channel equalization," in Digital communication, C. Palanisamy, ed., InTech, 2012.
  3. M. Pinchas, The whole story behind blind adaptive equalizers/blind deconvolution, Bentham Science Publishers, 2012. DOI: http://dx.doi.org/10.2174/97816080535201120101
  4. W. Rao, "New concurrent modulus algorithm and soft decision directed scheme for blind equalization," Procedia Environmental Sciences, vol. 10, pp. 1264-1269, 2011. DOI: http://dx.doi.org/10.1016/j.proenv.2011.09.202
  5. S. Chen and E.S. Chng, "Concurrent constant modulus algorithm and soft decision directed scheme for fractionally-spaced blind equalization," Proc. IEEE ICC, vol. 4, pp. 2342-2346, Jun. 2004. DOI: http://dx.doi.org/10.1109/icc.2004.1312937
  6. S. Chen, T.B. Cook, and L.C. Anderson, "A comparative study of two blind FIR equalizers," Digital Signal Processing, vol. 14, no. 1, pp. 18-36, Jan. 2004. DOI: http://dx.doi.org/10.1016/j.dsp.2003.04.001
  7. S. Haykin, Adaptive filter theory 5th Ed., Prentice Hall, New Jersey, 2013.
  8. J. Karaoguz and S. H. Ardalan, "A soft decision-directed blind equalization algorithm applied to equalization of mobile communication channels," Proc. IEEE ICC, vol. 3, pp. 1272-1276 , Jun. 1992. DOI: http://dx.doi.org/10.1109/icc.1992.268036
  9. E. Biglieri, J. Proakis, and S. Shamai, "Fading channels: information-theoretic and communications aspects," IEEE Trans. Inform. Theory, vol. 44, no. 6, pp. 2619-2692, Oct. 1998. DOI: http://dx.doi.org/10.1109/18.720551