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CDMA wireless system with blind multiuser detector

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Języki publikacji
EN
Abstrakty
EN
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.
Rocznik
Tom
Strony
69--75
Opis fizyczny
Bibliogr. 15 poz., il.
Twórcy
autor
autor
  • School of Information Technology, and Electrical Engineering, The University of Queensland, Brisbane QLD 4072, Australia and School of Electronics and Electrical Engineering, Imperial College London, South Kensington, SW7 2BT, United Kingdom, w.leong@imperial.ac.uk
Bibliografia
  • [1] A. Hyvarinen and E. Oja, “Independent component analysis: a tu-torial”, Tech. Rep., Helsinki University of Technology, Apr. 1999.
  • [2] A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis. Wiley, 2001.
  • [3] A. J. Bell and T. J. Sejnowski, “An information maximization ap-proach to blind separation and blind deconvolution”, Neur. Compu-tat., vol. 7, pp. 1129–1159, 1995.
  • [4] H. Delic and A. Hocann, “Robust detection in DS-CDMA”, IEEE Trans. Veh. Technol., vol. 51, pp. 155–170, 2002.
  • [5] H. Mathis, “Nonlinear functions for blind separation and equaliza-tion”, Ph.D. thesis, Hartung-Gorre, Konstanz, Nov. 2001.
  • [6] M. Honig, U. Madhow, and S. Verdu, “Blind adaptive multiuser detection”, IEEE Trans. Inform. Theory, vol. 41, pp. 944–960, 1995.
  • [7] P. Comon, “Independent component analysis, a new concept?”, Higher-Order Stat., vol. 36, no. 3, pp. 287–314, 1994.
  • [8] R. R. Coifman and D. L. Donoho, “Translation-invariant de-noising”, Tech. Rep., Yale University and Stanford University, 1995.
  • [9] D. Samardzija, N. Mandayam, and I. Seskar, “Blind successive inter-ference cancellation for DS-CDMA systems”, IEEE Trans. Commun., vol. 50, no. 2, pp. 276–290, 2002.
  • [10] S. Amari, “Natural gradient works efficiently in learning”, Neur. Computat., vol. 10, pp. 251–276, 1998.
  • [11] S. Amari, “Stability analysis of adaptive blind source separation”, Tech. Rep., Brain Information Processing Group, 1997.
  • [12] S. Verdu, “Adaptive multiuser detection”, in IEEE Third Int. Symp. Spr. Spectr. Tech. Appl. ISSSTA’94, Oulu, Finland, 1994, vol. 1, pp. 43–50.
  • [13] S. Verdu, Multiuser Detection, 2nd ed. Cambridge: Cambridge Uni-versity Press, 2001, chap. 2.
  • [14] T. Ristaniemi and J. Joutsensalo, “Advanced ICA-based receivers for blocking fading DS-CDMA channels”, Sig. Proces., vol. 82, pp. 417–431, 2002.
  • [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.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT3-0035-0033
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