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Article:Blind Adaptive Equalization of Complex Signals based on the Constant Modulus Algorithm

by D.R. Srinivas, K.E. Sreenivasa Murthy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 5
Year of Publication: 2010
Authors: D.R. Srinivas, K.E. Sreenivasa Murthy
10.5120/1580-2113

D.R. Srinivas, K.E. Sreenivasa Murthy . Article:Blind Adaptive Equalization of Complex Signals based on the Constant Modulus Algorithm. International Journal of Computer Applications. 11, 5 ( December 2010), 10-13. DOI=10.5120/1580-2113

@article{ 10.5120/1580-2113,
author = { D.R. Srinivas, K.E. Sreenivasa Murthy },
title = { Article:Blind Adaptive Equalization of Complex Signals based on the Constant Modulus Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 5 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 10-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number5/1580-2113/ },
doi = { 10.5120/1580-2113 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:29.106449+05:30
%A D.R. Srinivas
%A K.E. Sreenivasa Murthy
%T Article:Blind Adaptive Equalization of Complex Signals based on the Constant Modulus Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 5
%P 10-13
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper discuss, applicability of the second-order Newton gradient descent method for blind equalization of complex signals based on the Constant Modulus Algorithm (CMA). The Constant Modulus (CM) loss function is real with complex valued arguments, and, hence, non-analytic. The Hessian for noiseless FIR channels and rederive the known fact that the full Hessian of the CM loss function is always singular in a simpler manner. The channel model shows that the perfectly equalizing solutions are stationary points of the CM loss function and also evaluate the bit error rate. The paper also discuss of the full Newton method. Finally, to validate the proposed algorithm, simulation studies have been carried out and results are presented and compared. The simulation results show the effectiveness of the proposed algorithm.

References
  1. Y. Sato, “A method of self-recovering equalization for ultilevel amplitude- modulation systems,” IEEE Trans. Commun., vol. 23, no. 6, pp.679–682, Jun. 1975.
  2. D. N. Godard, “Self-recovering equalization and carrier tracking in two-dimensional data communications systems,” IEEE Trans. Commun., vol. 28, no. 11, pp. 1867–1875, Nov. 1980.
  3. J. R. Treichler and B. G. Agee, “A new approach to multipath correction of constant modulus signals,” IEEE Trans. Acoust., Speech, Signal Process., vol. 31, no. 2, pp. 459–472, Apr. 1983.
  4. G. H. Golub and C. F. van Loan, Matrix Computations,3rd ed. Baltimore, MD: Johns Hopkins Univ. Press, 1996.
  5. O. Dabeer and E. Masry, “Convergence analysis of the constant modulus Algorithm Onkar Dabeer, member,” IEEE Trans. Inf. Theory, vol. 49, no. 6, pp. 1447–1464, Jun. 2003.
  6. M. T. M. Silva and M. D. Miranda, “Tracking issues of some blind equalization algorithms,” IEEE Signal Process. Lett., vol. 11, no. 9 pp. 760–763, Sep. 2004.
  7. C. R. Johnson, Jr., P. Schniter, T. J. Edres, J. D. Behm, D. R. Brown, and R. A. Casas, “Blind equalization using the constant modulus criterion: A review,” Proc. IEEE, vol. 86, no. 10, pp. 1927–1950, Oct. 1998.
  8. G. Yan and H. Fan, “A Newton-like algorithm for complex variables with applications in blind equalization,” IEEE Trans. Signal Process. vol. 48, no. 2, pp. 553–556, Feb. 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Analytic functions blind equalization complex Newton method constant modulus algorithm (CMA)