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Self-Organizing Map for Blind Channel Equalization

  • Han, Soo-Whan (Department of Multimedia Eng., Dongeui University)
  • Received : 2010.10.28
  • Accepted : 2010.11.23
  • Published : 2010.12.31

Abstract

This paper is concerned with the use of a selforganizing map (SOM) to estimate the desired channel states of an unknown digital communication channel for blind equalization. The modification of SOM is accomplished by using the Bayesian likelihood fitness function and the relation between the desired channel states and channel output states. At the end of each clustering epoch, a set of estimated clusters for an unknown channel is chosen as a set of pre-defined desired channel states, and used to extract the channel output states. Next, all of the possible desired channel states are constructed by considering the combinations of extracted channel output states, and a set of the desired states characterized by the maximal value of the Bayesian fitness is subsequently selected for the next SOM clustering epoch. This modification of SOM makes it possible to search the optimal desired channel states of an unknown channel. In simulations, binary signals are generated at random with Gaussian noise, and both linear and nonlinear channels are evaluated. The performance of the proposed method is compared with those of the "conventional" SOM and an existing hybrid genetic algorithm. Relatively high accuracy and fast search speed have been achieved by using the proposed method.

Keywords

References

  1. Z. Ding and L. Ye, Blind Equalization and Identification, New York: Marcel Dekker, 2001.
  2. H. Gazzah and K. A. Meraim, "Blind ZF equalization with controlled delay robust to order over estimation," Signal Processing, vol. 83, pp. 1505-1518, 2003. https://doi.org/10.1016/S0165-1684(03)00070-7
  3. J. Zhu, XR Cao and RW. Liu, "A blind fractionally spaced equalizer using higher order statistics," IEEE Transactions on. Circuits and Systems. II: Analog Digital Signal Process, vol. 46, pp. 755-764, 1999. https://doi.org/10.1109/82.769783
  4. E. Serpedin and G.B. Giannakis, "Blind channel identification and equalization with modulation-induced cyclostationarity," IEEE Transactions on Signal Processing, vol. 46, pp. 1930-1944, 1998 https://doi.org/10.1109/78.700965
  5. Y. Fang, W.S. Chow and K.T. Ng, "Linear neural network based blind equalization," Signal Processing, vol. 76, pp. 37-42, 1999. https://doi.org/10.1016/S0165-1684(98)00245-X
  6. Yun Ye and Saman S. Abeysekera, "Efficient blind estimation and equalization of non-minimum phase communication channels via the use of a zero forcing equalizer," Signal Processing, vol. 86, pp.1019-1034, 2006. https://doi.org/10.1016/j.sigpro.2005.07.021
  7. S. Mo and B. Shafai, "Blind equalization using higher order cumulants and neural networks," IEEE Transactions on Signal Processing, vol.42, pp.3209-3217, 1994 https://doi.org/10.1109/78.330378
  8. X. H. Dai, "CMA-based nonlinear blind equaliser modelled by a two-layer feedforward neural network," IEE Proceedings: Communications, vol. 148, pp. 243-248, 2001. https://doi.org/10.1049/ip-com:20010269
  9. T. Stathaki and A. Scohyers, "A constrained optimization approach to the blind estimation of Volterra kernels," Proc. of the IEEE International Conference on ASSP, vol. 3, pp. 2373-2376, 1997.
  10. T. Stathaki and A. Scohyers, "A constrained optimization approach to the blind estimation of Volterra kernels," Proc. of the IEEE International Conference on ASSP, vol. 3, pp. 2373-2376, 1997. https://doi.org/10.1109/26.297849
  11. G.K. Kaleh and R. Vallet, "Joint parameter estimation and symbol detection for linear or nonlinear unknown channels," IEEE Trans. Commun., vol. 42, pp. 2406-2413, 1994. https://doi.org/10.1109/26.297849
  12. D. Erdogmus, D. Rende, J.C. Principe and T.F. Wong, "Nonlinear channel equalization using multilayer perceptrons with information theoretic criterion," Proc. of IEEE workshop Neural Networks and Signal Processing, pp. 443-451, MA, U.S.A., 2001. https://doi.org/10.1109/TSP.2004.827176
  13. I. Santamaria, C. Pantaleon, L. Vielva and J. Ibanez, "Blind equalization of constant Modulus signals using support vector machines," IEEE Transactions on Signal Processing, vol. 52, pp. 1773-1782, 2004. https://doi.org/10.1109/TSP.2004.827176
  14. G. Raz and B. Van Veen, "Blind equalization and identification of nonlinear and IIR systems - a least squares approach," IEEE Transactions on Signal Processing, vol. 48, pp. 192-200, 2000. https://doi.org/10.1109/78.815489
  15. H. Lin and K. Yamashita, "Hybrid simplex genetic algorithm for blind equalization using RBF networks," Mathematics and Computers in Simulation, vol. 59, pp. 293-304, 2002. https://doi.org/10.1016/S0378-4754(01)00364-0
  16. S. Han, W. Pedrycz and C. Han, "Nonlinear Channel Blind Equalization Using Hybrid Genetic Algorithm with Simulated Annealing," Mathematical and Computer Modeling, vol. 41, pp. 697-709, 2005. https://doi.org/10.1016/j.mcm.2004.05.006
  17. T. Kohonen, Self-organization and Associative Memory (3rd ed.), Berlin: Springer-Verlag, 1989.
  18. T. Kohonen, K. Raivio, O. Simula, O. Venta, and J. Henriksson, "Combining linear equalization and self-organizing adaptation in dynamic discrete-signal detection," Proc. of the International Joint Conference on Neural Networks, vol. 1, pp. 223-228, 1990.
  19. G. A. Barreto and L. G. M. Souza, "Adaptive filtering with the selforganizing map: A performance comparison," Neural Networks, vol. 19, pp. 785–798, 2006. https://doi.org/10.1016/j.neunet.2006.05.005
  20. R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis, Wiley, New York, 1973.
  21. S. Chen, B. Mulgrew and S. McLaughlin, "Adaptive Bayesian equalizer with decision feedback," IEEE Tranactions on Signal Processing, vol. 41, pp. 2918-2927, 1993. https://doi.org/10.1109/78.236513
  22. S. Chen, B. Mulgrew and M. Grant, "A clustering technique for digital communication channel equalization using radial basis function network," IEEE Transactions on. Neural Networks, vol. 4, pp. 570-579, 1993. https://doi.org/10.1109/72.238312
  23. L. Fausett, Fundamentals of Neural Networks, New Jersey: Prentice-Hall, 1994.
  24. H. Lin and K. Yamashita, "Blind equalization using parallel Bayesian decision feedback equalizer," Mathematics and Computers in Simulation, vol. 56, pp. 247-257, 2001. https://doi.org/10.1016/S0378-4754(01)00276-2