CDMA wireless system with blind multiuser detector
DOI:
https://doi.org/10.26636/jtit.2006.1.355Keywords:
code division multiple access, independent component analysis, blind source separationAbstract
In this paper we present an approach capable of countering the presence of multiple access interference (MAI) in code division multiple access (CDMA) channels. We develop and implement a blind multiuser detector, based on an independent component analysis (ICA) to mitigate both MAI and noise. This algorithm has been utilized in blind source separation (BSS) of unknown sources from their linear mixtures. It can also be used for estimation of the basis vectors of BSS. The aim is to include an ICA algorithm within a wireless receiver in order to reduce the level of interference in CDMA systems. This blind multiuser detector requires less precise knowledge of the channel than does the conventional single-user receiver. The proposed blind multiuser detector is made robust with respect to imprecise knowledge of the received signature waveforms of the user of interest. Several experiments are performed in order to verify the validity of the proposed learning algorithm.
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[1] A. Hyvärinen and E. Oja, "Independent component analysis: a tutorial", Tech. Rep., Helsinki University of Technology, Apr. 1999.
View in Google Scholar
[2] A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. Wiley, 2001.
View in Google Scholar
[3] A. J. Bell and T. J. Sejnowski, "An information maximization approach to blind separation and blind deconvolution", Neur. Computat., vol. 7, pp. 1129-1159, 1995.
View in Google Scholar
[4] H. Delic and A. Hocanin, "Robust detection in DS-CDMA", IEEE Trans. Veh. Technol., vol. 51, pp. 155-170, 2002.
View in Google Scholar
[5] H. Mathis, "Nonlinear functions for blind separation and equalization", Ph.D. thesis, Hartung-Gorre, Konstanz, Nov. 2001.
View in Google Scholar
[6] M. Honig, U. Madhow, and S. Verdú, "Blind adaptive multiuser detection", IEEE Trans. Inform. Theory, vol. 41, pp. 944-960, 1995.
View in Google Scholar
[7] P. Comon, "Independent component analysis, a new concept?", Higher-Order Stat., vol. 36, no. 3, pp. 287-314, 1994.
View in Google Scholar
[8] R. R. Coifman and D. L. Donoho, "Translation-invariant denoising", Tech. Rep., Yale University and Stanford University, 1995.
View in Google Scholar
[9] D. Samardzija, N. Mandayam, and I. Seskar, "Blind successive interference cancellation for DS-CDMA systems", IEEE Trans. Commun., vol. 50, no. 2, pp. 276-290, 2002.
View in Google Scholar
[10] S. Amari, "Natural gradient works efficiently in learning", Neur. Computat., vol. 10, pp. 251-276, 1998.
View in Google Scholar
[11] S. Amari, "Stability analysis of adaptive blind source separation", Tech. Rep., Brain Information Processing Group, 1997.
View in Google Scholar
[12] S. Verdú, "Adaptive multiuser detection", in IEEE Third Int. Symp. Spr. Spectr. Tech. Appl. ISSSTA'94, Oulu, Finland, 1994, vol. 1, pp. 43-50.
View in Google Scholar
[13] S. Verdú, Multiuser Detection, 2nd ed. Cambridge: Cambridge University Press, 2001, chap. 2.
View in Google Scholar
[14] T. Ristaniemi and J. Joutsensalo, "Advanced ICA-based receivers for blocking fading DS-CDMA channels", Sig. Proces., vol. 82, pp. 417-431, 2002.
View in Google Scholar
[15] X. D. Zhang and W. Wei, "Blind adaptive multiuser detection based on Kalman filtering", IEEE Trans. Sig. Proces., vol. 50, no. 1, pp. 87-95, 2002.
View in Google Scholar
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