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Performance Comparison of S-MMA Adaptive Equalization Algorithm by Slice Weighting Value in 16-QAM Signal

16-QAM 신호에서 Slice 가중치에 의한 S-MMA 적응 등화 알고리즘의 성능 비교

  • Lim, Seung-Gag (Dept. of Information and Communication, Kongju National University)
  • 임승각 (공주대학교 정보통신공학부 정보통신공학)
  • Received : 2013.02.25
  • Accepted : 2013.06.14
  • Published : 2013.06.30

Abstract

This paper compare the performance of S-MMA(Sliced-MultiModulus Algorithm) adaptive equalization algorithm by effect of slice weighting value for the minimization of the distortion and noise in the communication channel.. In the traditional MMA algorithm, the output signal of equalizer and the dispersion constant of transmitting signal is used for calculating the equalizer coefficient, but in S-MMA, the output of equalizer and dispersion constant and the considering the output of decision device by the power of slice constant are used in order to simultaneously compensate the distortion of amplitude and phase distortion. It is confirmed by computer simulation that the slice weighting value affects the performance of adaptive equalization algorithm. The performance index includes the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER according to the signal and noise power ratio at the channel is used. As a result of simulation, the residual isi, maximum distortion and MSE performances are better in the small weighting values. But in SER performance is better in the large weighting values.

본 논문에서는 통신 채널에서 발생되는 찌그러짐과 잡음의 영향을 최소화하기 위하여 사용되는 S-MMA 적응 등화 알고리즘에서 Slice 가중치에 따른 성능을 비교하였다. 기존의 MMA 알고리즘에서는 등화기의 출력 신호와 송신 신호의 dispersion 상수만을 이용하지만, S-MMA에서는 등화기 출력 신호와 dispersion 상수외에 결정 장치의 출력 신호를 slice 상수만큼 고려하여 채널의 진폭과 위상 찌그러짐을 동시에 보상할 수 있다. 이때 slice 가중치가 적응 등화 알고리즘의 성능에 미치는 영향을 컴퓨터 시뮬레이션을 통해 확인하며, 성능 지수로는 등화기 출력 신호 성상도, 수렴 특성을 나타내는 잔류 isi, 최대 찌그러짐, MSE와 채널의 신호대 잡음비에 따른 SER을 사용하였다. 시뮬레이션 결과 slice 가중치가 적으면 잔류isi, 최대 찌그러짐과 MSE 성능이 우월하며, 가중치가 큰 경우 SER 성능이 우월함을 확인하였다.

Keywords

References

  1. D.N.Godard, "Self-recovering Equalization and carrier tracking in two-dimensional data comm. system", IEEE Trans. on Comm., Vol. 28, pp.1867-1875, Nov. 1980 https://doi.org/10.1109/TCOM.1980.1094608
  2. J.Yang, J.J.Werner, G.A.Dumont, "The Multimodulus Blind Equalization and Its Generalized Algorithms", IEEE Journal on S.A.C., Vol.20, No.3, pp.997- 1015, June 2002
  3. S.G.Lim, "The Performance Comparison of the CMA and MMA Algorithm for Blind Adaptive Equalization", Jour. of I.W.I.T., Vol. 12, No.2, pp.153-158, April 2012
  4. S.G.Lim, "The Performance Comparison of the MMA and SCA Algorithm for Self Adaptive Eqaulization", Jour. of I.W.I.T., Vol. 12, No. 2, pp. 159-165, April 2012
  5. J.Yang, J.J.Werner, G.A.Dumont, "The Multimodulus Blind Equalization Algorithm", 13th International Conf. on D.S.P Proceeding Vol.1, pp.127-130, 1997
  6. S.A.Sheikh, P.Fan, "A New Multimodulus Blind Equalizer for Dense QAM Constellation", International Conf. on Wireless, Mobile and Multimedia networks, pp.1-4, 2006
  7. S.Abrar, R.A.Axfort, "Sliced Multi-modulus Blind Equalization Algorithm", ETRI Journal, Vol. 27, No. 3, June 2005
  8. W.A.Sethares, G.A.Rey, JR.C.R.Johnson, "Approach to Blind Equalization of Signal with Multile Modulus", IEEE Proc. ICASSP, pp.972-975, Apr. 1989
  9. J.T.Yuan, T.C.Lin, "Equalization and Carrier Phase Recovery of CMA and MMA in blind adaptive Receiver", IEEE Trans. on S.P., Vol. 58, No. 6, pp.3206-3217, June 2010 https://doi.org/10.1109/TSP.2010.2044255
  10. X.L.Li, W.J.Zeng, "Performance Analysis and Adaptive Newton Algorithms of Multimodulus Blind Equalization Criterion", Signal Processing, Vol. 89, pp.2263-2273, Nov. 2009 https://doi.org/10.1016/j.sigpro.2009.05.003
  11. K.N.Oh, "An Algorithm for Variable Step-Size Improving Steady-State Performance of Blind Equalization", Jour. of K.I.I.T., Vol. 9, No. 10, pp.43-48, Oct. 2011