Blind multiuser detection for long-code CDMA systems with transmission-induced cyclostationarity

  • Authors:

  • Tongtong Li;Weiguo Liang;Zhi Ding;Jitendra K. Tugnait

  • Affiliations:

  • Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI;Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI;Department of Electrical and Computer Engineering, University of California, Davis, CA;Department of Electrical and Computer Engineering, Auburn University, Auburn, AL

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on advanced signal processing algorithms for wireless communications
  • Year:
  • 2005

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Abstract

We consider blind channel identification and signal separation in long-code CDMA systems. First, by modeling the received signals as cyclostationary processes with modulation-induced cyclostationarity, long-code CDMA system is characterized using a time-invariant system model. Secondly, based on the time-invariant model, multistep linear prediction method is used to reduce the intersymbol interference introduced by multipath propagation, and channel estimation then follows by utilizing the nonconstant modulus precoding technique with or without the matrix-pencil approach. The channel estimation algorithm without the matrix-pencil approach relies on the Fourier transform and requires additional constraint on the code sequences other than being a nonconstant modulus. It is found that by introducing a random linear transform, the matrix-pencil approach can remove (with probability one) the extra constraint on the code sequences. Thirdly, after channel estimation, equalization is carried out using a cyclic Wiener filter. Finally, since chip-level equalization is performed, the proposed approach can readily be extended to multirate cases, either with multicode or variable spreading factor. Simulation results show that compared with the approach using the Fourier transform, the matrix-pencil-based approach can significantly improve the accuracy of channel estimation, therefore the overall system performance.