Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지

A Modified FCM for Nonlinear Blind Channel Equalization using RBF Networks

  • Han, Soo-Whan (Department of Multimedia Eng., Dongeui University)
  • Published : 2007.03.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

Keywords

References

  1. E. Biglieri, A. Gersho, R. D. Gitlin and T. L. Lim, 'Adaptive cancellation of nonlinear intersymbol interference for voiceband data transmission,' IEEE J. Selected Areas Commun. SAC-2(5), 1984, pp. 765-777
  2. Proakis, J. G., Digital Communications, Fourth Edition, McGraw-Hill, New York, 2001
  3. X. R. Cao and J. Zhu, 'Blind equalization with a linear feedforward neural network,' Proc. 5th European Symp. on Artificial Neural Networks, Bruges, Belgium, 1997, pp. 267-272
  4. E. Serpedin and G. B. Giannakis, 'Blind channel identification and equalization with modulation-induced cyclostationarity,' IEEE Trans. Siganl Processing, vol. 46,1998, pp. 1930-1944 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, 1999, pp. 37-42 https://doi.org/10.1016/S0165-1684(98)00245-X
  6. T. Stathaki and A. Scohyers, 'A constrained optimization approach to the blind estimation of Volterra kernels,' Proc. IEEE Int. Conf. on ASSP, vol. 3,1997, pp. 2373-2376
  7. G. K. Kaleh and R. Vallet, 'Joint parameter estimation and symbol detection for linear or nonlinear unknown channels,' IEEE Trans. Commun., vol. 42, 1994, pp. 2406-2413 https://doi.org/10.1109/26.297849
  8. 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, MA, U.S.A., 2001, pp.443-451
  9. X. Liu and T. Adaly, 'Canonical piecewise linear network for nonlinear filtering and its application to blind equalization,' Signal Processing, vol. 61, 1997, pp. 145-155 https://doi.org/10.1016/S0165-1684(97)00099-6
  10. I. Santamaria, C. Pantaleon, L. Vielva and J. Ibanez, 'Blind Equalization of Constant Modulus Signals Using Support Vector Machines,' IEEE Trans. Signal Processing, vol. 52, 2004, pp. 1773-1782 https://doi.org/10.1109/TSP.2004.827176
  11. H. Lin and K. Yamashita, 'Hybrid simplex genetic algorithm for blind equalization using RBF networks,' Mathematics and Computers in Simulation, vol. 59, 2002, pp. 293-304 https://doi.org/10.1016/S0378-4754(01)00364-0
  12. Soowhan Han, Imgeun Lee and Changwook Han, 'A New Hybird Genetic Algorithm for Nonlinear Channel Blind Equalization,' International Journal of Fuzzy Logic and Intelligent Systems, 2004, pp. 259-265
  13. J.C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum Press, New York, 1981
  14. S. Chen, B. Mulgrew and P. M. Grant, 'A Clustering Technique for Digital Communications Channel Equalization Using Radial Basis Function Networks,' IEEE Trans. Neural Networks, vol. 4, 1993, pp. 570-579 https://doi.org/10.1109/72.238312
  15. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, New York, Wiley, 1973
  16. J. Lee, C. Beach and N. Tepedelenlioglu, 'Channel Equalization using Radial Basis Function Network,' ICASSP, vol. 3, Atlanta, Georgia, U.S.A., 1996, pp. 1719-1722
  17. H. Lin and K. Yamashita, 'Blind equalization using parallel Bayesian decision feedback equalizer,' Mathematics and Computers in Simulation, vol. 56, 2001, pp. 247-257 https://doi.org/10.1016/S0378-4754(01)00276-2