Advertisement

Modified Hopfield Neural Network for CDMA Multiuser Detection

  • Xiangdong Liu
  • Xuexia Wang
  • Zhilu Wu
  • Xuemai Gu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

Abstract

We investigate the application of modified Hopfield neural networks (HNNs) based on Annealing Techniques to the problem of multiuser detection in spread spectrum CDMA communication systems. It is shown that the NP-complete problem of minimizing the objective function of the optimal multiuser detector (OMD) can be translated into minimizing an HNN “energy” function, thus allowed to take advantage of the ability of HNNs to perform very fast gradient descent algorithms in analog hardware. The performance of the proposed HNN receiver is evaluated via computer simulations and compared to that of the general HNN as well as to that of the OMD for CDMA transmission cases. It is shown that the modified HNN detection scheme exhibits a number of attractive properties and that it provides in fact more powerful performance than the general HNN scheme or the OMD scheme.

Keywords

Code Division Multiple Access Successive Interference Cancellation Hopfield Neural Network Code Division Multiple Access System Hopfield Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Verdu, S.: Multiuser Detection. Cambridge University Press, Cambridge (1984)Google Scholar
  2. 2.
    Yoon, S.H., Rao, S.: Multiuser detection in CDMA Based on the Annealed Neural Network. IEEE Int. Conf. Neural Networks 4, 2124–2129 (1996)Google Scholar
  3. 3.
    Chen, D.C., Sheu, B.J.: A Compact Neural network Based CDMA Receiver for Multimedia Wireless Communication. IEEE Conf. Comp. Design, 99–103 (1996)Google Scholar
  4. 4.
    Kechriotis, G.I., Manolakos, E.S.: Implementing the Optimal CDMA Multiuser Detector with Hopfield Neural network. IEEE Workshop on Appl. Neural Networks and telecomm., 60–66 (1993)Google Scholar
  5. 5.
    Verdu, S.: Computational Complexity of Optimum Multiuser Detection. Algorithmica 4, 303–312 (1998)CrossRefMathSciNetGoogle Scholar
  6. 6.
    Hopfield, J.J.: Neurons with Graded Response Have Collective Computational Properties like Those of Two-stage Neurons. Proc. Nat. Acad. Sci. 81, 3088–3092 (1984)CrossRefGoogle Scholar
  7. 7.
    Jeney, G., Levendovezky, J., Imre, S., Pap, L.: Comparison of Different Neural Network Based Multiuser Detector. In: EUNICE 2000, Enschede, pp. 117–123 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiangdong Liu
    • 1
  • Xuexia Wang
    • 1
  • Zhilu Wu
    • 1
  • Xuemai Gu
    • 1
  1. 1.School of Electronics and Information TechnologyHarbin Institute of TechnologyHarbinChina

Personalised recommendations