ETRI Journal

  • 제31권2호
  • /
  • Pages.162-172
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  • 2009
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  • 1225-6463(pISSN)
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  • 2233-7326(eISSN)
한국전자통신연구원 (Electronics and Telecommunications Research Institute)
권호 표지

Blind MMSE Equalization of FIR/IIR Channels Using Oversampling and Multichannel Linear Prediction

  • Chen, Fangjiong (School of Electronic and Information Engineering, South China University of Technology) ;
  • Kwong, Sam (Department of Computer Science, City University of Hong Kong) ;
  • Kok, Chi-Wah (Department of Computer Science, City University of Hong Kong)
  • 투고 : 2008.03.06
  • 심사 : 2009.02.10
  • 발행 : 2009.04.30
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초록

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

키워드

참고문헌

  1. F. Chen et al., “Blind IIR Channel Equalization Based on Second Order Statistics,” IEEE Vehicular Technology Conference, May 2006, pp. 2334-2338.
  2. Z. Ding and Y. Li, Blind Equalization and Identification, Marcel Dekker, 2001.
  3. R. Johnson, “Admissibility in Blind Adaptive Channel Equalization,” IEEE Contr. Syst. Mag., Jan. 1991, pp. 3-15.
  4. C.Y. Chi et al., “Batch Processing Algorithms for Blind Equalization Using Higher-Order Statistics,” IEEE Signal Processing Magazine, vol. 20, no. 1, Jan. 2003, pp. 25-49. https://doi.org/10.1109/MSP.2003.1166627
  5. L. Tong et al., “Blind Identification and Equalization Based on Second-Order Statistics: A Frequency Domain Approach,” IEEE Tran. Information Theory, vol. 41, no. 1, Jan. 1995, pp. 329-334. https://doi.org/10.1109/18.370088
  6. K. Abed-Meraim, E. Moulines, and P. Loubaton, “Prediction Error Method for Second-Order Blind Identification,” IEEE Trans. on Signal Processing, vol. 45, no. 3, Mar. 1997, pp. 694-705. https://doi.org/10.1109/78.558487
  7. J. Shen and Z. Ding, ”Direct Blind MMSE Channel Equalization Based on Second-Order Statistics,” IEEE Trans. on Signal Processing, vol. 48, no. 4, Apr. 2000, pp. 1015-1023. https://doi.org/10.1109/78.827535
  8. X. Li and H. Fan, ”Direct Estimation of Blind Zero-Forcing Equalizers Based on Second-Order Statistics,” IEEE Trans. on Signal Processing, vol. 48, no. 8, Aug. 2000, pp. 2211-2218. https://doi.org/10.1109/78.852002
  9. X. Li and H. Fan, “Linear Prediction Methods for Blind Fractionally Spaced Equalization,” IEEE Trans. Signal Processing, vol. 48, June 2000, pp. 1667-1675. https://doi.org/10.1109/78.845924
  10. G.B. Giannakis and S.D.Halford, “Blind Fractionally Spaced Equalization of Noisy FIR Channels: Direct and Adaptive Solutions,” IEEE Trans. Signal Processing, vol. 45, Sept. 1997, pp. 2277-2292. https://doi.org/10.1109/78.622950
  11. W.B. Braun and U. Dersch, “A Physical Mobile Radio Channel Model,” IEEE Trans. Vehicular Technology, vol. 40, no. 2, May 1991, pp. 472-482. https://doi.org/10.1109/25.289429
  12. A.J. Paulraj et al., “An Overview of MIMO Communication: A Key to Gigabit Wireless.” Proc. of the IEEE, vol. 92, no. 2, Feb. 2004, pp. 198-218.
  13. A. Tkacenko and P.P. Vaidyanathan, “A Low-Complexity Eigenfilter Design Method for Channel Shortening Equalizers for DMT Systems,” IEEE Trans. Communication, vol. 51, no. 7, July 2003, pp. 1069-1072, July 2003. https://doi.org/10.1109/TCOMM.2003.814235
  14. S.E. El-Khamy, H. El-Ragal, and A.A, El-Sherif, “A Modified Elgen Approach Method for the Design of Channel Shortening Equalizers in Discrete Multi-tone Systems,” The 22th National Radio Science Conference, NRSC, Mar. 2005, pp. 367-376.
  15. E. Bai and M. Fu, “Blind System Identification and Channel Equalization of IIR Systems Without Statistical Information,” IEEE Trans. Signal Process, vol. 47, no. 7, July 1999, pp. 1910-1921. https://doi.org/10.1109/78.771040
  16. K. Vanbleu, M. Moonen, and G. Leus, “Linear and Decision Feedback Per Tone Equalization for DMT-Based Transmission Over IIR Channels,” IEEE Trans. Signal Processing, vol. 54, no. 1, Jan. 2006, pp. 258-273. https://doi.org/10.1109/TSP.2005.859254
  17. G.M. Raz and B.D. Van Veen, “Blind Equalization and Identification of Nonlinear and IIR Systems: A Least Squares Approach,” IEEE Trans. Signal Process, vol. 48, no. 1, Jan. 2000, pp. 192-200. https://doi.org/10.1109/78.815489
  18. J.K. Tugnait, “Multistep Linear Predictors-Based Blind Equalization of FIR/IIR Single-Input Multiple-Output Channels with Common Zeros,” IEEE Trans. Signal Processing, vol. 47, June 1999, pp. 1689-1700. https://doi.org/10.1109/78.765141
  19. F. Chen et al., “Blind Linear Channel Estimation Using Genetic Algorithm and SIMO Model,” Signal Processing, vol. 83, no. 9, Sept. 2003, pp. 2021-2035. https://doi.org/10.1016/S0165-1684(03)00133-6
  20. V. Sharma and V.N. Raj, “Convergence and Performance Analysis of Godard Family and Multimodulus Algorithms for Blind Equalization,” IEEE Trans. Signal Processing, vol. 53, no. 4, Apr. 2005, pp. 1520-1533 https://doi.org/10.1109/TSP.2005.843725
  21. J. Yang, J.J. Werner, and G.A. Dumont, “The Multimodulus Blind Equalization and Its Generalized Algorithms,” IEEE J. Selected Areas in Commu., vol. 20, no. 5, June 2002, pp. 997-1015. https://doi.org/10.1109/JSAC.2002.1007381