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Robust Blind Multiuser Detection Algorithm Using Fourth-Order Cumulant Matrices

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Abstract

A new blind detection algorithm, based on fourth-order cumulant matrices, is presented and applied to the multiuser symbol estimation problem in direct sequence code division multiple access (DS-CDMA) systems. The blind detection is to estimate multiple symbol sequences in the downlink of a DS-CDMA communication system using only the received wireless data and without any knowledge of the user spreading codes. The proposed algorithm takes advantage of higher cumulant matrix properties to reduce the computational load and enhance the performance. Bit error rate simulations of this algorithm are performed for different numbers of users, signal-to-noise ratios, and numbers of symbols per user in comparison with the FastICA and RobustICA algorithms. The results show that the proposed algorithm outperforms both ICA-based detectors in estimating the symbol signals from the received mixed signals. Moreover, the proposed blind detector is computationally fast and exhibits high convergence speed in extracting user symbols.

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References

  1. Z. Albataineh, F. Salem, New blind multiuser detection DS-CDMA algorithm using simplified fourth order cumulant matrices, in IEEE International Symposium on Circuit and System (ISCAS), (IEEE, 2013), pp. 1946–1949

  2. Z. Albataineh, F. Salem, New blind multiuser detection DS-CDMA algorithm using H-DE and ICA algorithms, in 4th International Conference on Intelligent Systems Modelling and Simulation (ISMS), (IEEE, 2013), pp. 569–574

  3. Z. Albataineh, F. Salem, Blind multiuser detection DS-CDMA algorithm on the fast relative newton algorithm, in textitWireless telecommunication symposium (WTS), (IEEE, 2014), pp. 1–5

  4. Z. Albataineh, F. Salem, New blind multiuser detection DS-CDMA algorithm based on Extension of Efficient FAST Independent Component Analysis (EF-ICA), in 4th International Conference on Intelligent Systems Modelling and Simulation (ISMS), (ISMS, 2013), pp. 543–548

  5. A. Bayati, S. Prakriya, S. Prasad, Semi-blind space-time receiver for multiuser detection of DS/CDMA signals in multipath channels. Inst. Eng. Technol. 153(3), 410–418 (2006)

    Google Scholar 

  6. A.J. Bell, T.J. Sejnowski, An information maximization approach to blind separation and blind deconvolution. Neural Comput. 7(6), 1129–1159 (1995)

    Article  Google Scholar 

  7. J.F. Cardoso, On the performance of orthogonal source separation algorithms, in Proceedings of EUSIPCO, (1994a), pp. 776–779

  8. J.-F. Cardoso, High-order contrasts for independent component analysis. Neural Comput. 11(1), 157–192 (1999)

    Article  MathSciNet  Google Scholar 

  9. J.-F. Cardoso, A. Souloumiac, Blind beamforming for non Gaussian signals. IEEE Proc.-F 140(6), 362–370 (1993)

    Google Scholar 

  10. S. Choi, A. Cichocki, S. Amari, Flexible independent component analysis. J. VLSI Signal Process. 26(1–2), 25–38 (2000)

    Article  MATH  Google Scholar 

  11. A. Cichocki, S. Amari, Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications (Wiley, New York, 2002)

    Book  Google Scholar 

  12. P. Comon, C. Jutten (eds.), Handbook of Blind Source Separation Independent Component Analysis and Applications, (Academic Press, Oxford, 2010)

  13. P. Comon, Independent component analysis, a new concept. Signal Process. (Special Issue on Higher-Order Statistics) 36(3), 287–314 (1994)

    MATH  Google Scholar 

  14. R.C. Delamare, R. Sampaio Neto, Blind adaptive code-constrained constant modulus algorithms for CDMA interference suppression in multipath channels. IEEE Commun. Lett. 9(4), 334–336 (2005)

    Google Scholar 

  15. M. Gupta, B. Santhanam, ICA based blind adaptive MAI suppression in DS-CDMA systems, in Taos Ski Valley, Proceedings of IEEE-DSP Workshop (IEEE, Taos Ski Valley, 2004), pp. 201–205

  16. L. Hu, X. Zhou, L. Zhang, Blind multiuser detection based on Tikhonov regularization. IEEE Commun. Lett. 15(5), 482–484 (2011)

    Article  Google Scholar 

  17. A. Hyvarinen, A.E. Oja, A fast fixed-point algorithm for independent component analysis. Neural Comput. 9(7), 1483–1492 (1997)

    Article  Google Scholar 

  18. A. Hyvarinen, Fast and robust fixed-point algorithm for independent component analysis. IEEE Trans. Neural Netw. 10(3), 626–634 (1999)

    Article  Google Scholar 

  19. A. Hyvarinen, E. Oja, Independent component analysis: algorithms and applications. Neural Netw. 13(48–55), 411–430 (2000)

    Article  Google Scholar 

  20. A. Kachenoura, L. Albera, L. Senhadji, P. Comon, ICA: a potential tool for BCI systems. IEEE Signal Process. Mag. 25(1), 57–68 (2008)

    Article  Google Scholar 

  21. T. Koivisto, V. Koivunen, Blind despreading of short-code DS-CDMA signals in asynchronous multi-user systems. Signal Process. 11(87), 2560–2568 (2007)

    Article  Google Scholar 

  22. X. Liu, R.B. Randall, A new efficient independent component algorithm: joint approximate diagonalization of simplified cumulant matrices, in The 16th National Congress of Australian Institute of Physics, (Canberra, 2005)

  23. D. Nion, L. De Lathauwer, A block component model-based blind DS-CDMA receiver. IEEE Trans. Signal Process. 56, 5567–5579 (2008)

    Article  MathSciNet  Google Scholar 

  24. E. Ollila, The deflation-based fastICA estimator: Statistical analysis revisited. IEEE Trans. Signal Process. 58(3), 1527–1541 (2010)

    Article  MathSciNet  Google Scholar 

  25. E. Oja, Z. Yuan, The fast ICA algorithm revisited: convergence-analysis. IEEE Trans. Neural Netw. 17(6), 1370–1381 (2006)

    Article  Google Scholar 

  26. S.D. Parmar, B. Unhelkar, Separation performance of ICA algorithms in communication systems, in IMPACT’09, Multimedia, Signal Processingand Communication Technologies, (2009), pp. 142–145

  27. P.-Y. Qiu, Z.-T. Huang, W.-L. Jiang, C. Zhang, Improved blind spreading sequence estimation algorithm for the direct sequence spread spectrum signals JIET. Signal Process. 2(2), 139–146 (2008)

    Google Scholar 

  28. H. Rutishauser, The Jacobi method for real symmetric matrices. Numer. Math. 9, 1–10 (1966)

    Article  MathSciNet  MATH  Google Scholar 

  29. F.M. Salam, G. Erten, The state space framework for blind dynamic signal extraction and recovery, Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS’, 99), vol. 5, (IEEE, 1999), pp. 66–69

  30. L. Shen, S. Li, F. Chen, J. Wei, Blind multi-user detection in DS-CDMA downlink under gaussian noise using independent component analysis, in 8th International Conference on Signal Processing, (Beijing, 2006), pp. 1–6

  31. J.K. Tugnait, J. Ma, Blind multiuser receiver for space-time coded CDMA signals in frequency-selective channels. IEEE Trans. Wirel. Commun. 3(5), 1770–1780 (2004)

    Article  Google Scholar 

  32. M.K. Tsatsanis, Z. Xu, Performance analysis of minimum variance CDMA receivers. IEEE Trans. Signal Process. 46(11), 3014–3022 (1998)

    Article  Google Scholar 

  33. K. Waheed, K. Desai, F.M. Salem, Blind multi user detection in DS-CDMA systems using natural gradient based symbol recovery structures, in Proceedings of 4th International Conference on Independent Component Analysis and Blind Signal Separation, (2003), pp. 727–732

  34. K. Waheed, K. Desai, F.M. Salem, Natural gradient based blind multi user detection in QPSK DS-CDMA systems, in Proceedings of IEEE-INNS Joint International Conference Neural Networks, vol 3, (IEEE, 2003), pp. 1862–1867

  35. K. Waheed, F. Salem, Blind information-theoretic multiuser detection algorithms for DS-CDMA and WCDMA downlink systems. IEEE Trans. Neural Netw. 16(4), 937–948 (2005)

    Article  Google Scholar 

  36. Y. Washizawa, Y. Yamashita, T. Tanaka, A. Cichocki, Blind extraction of global signal from multi-channel noisy observations. IEEE Trans. Neural Netw. 21(9), 1472–1481 (2010)

    Article  Google Scholar 

  37. L. Xianhua, J.-F. Cardoso, R.B. Randall, Very fast blind source separation by signal to noise ratio based stopping threshold for the SHIBBS/SJAD algorithm. Mech. Syst. Signal Process. 24(7), 2096–2103 (2010)

    Article  Google Scholar 

  38. C. Xu, G. Feng, K.S. Kwak, A modified constrained constant modulus approach to blind adaptive multiuser detection. IEEE Trans. Commun. 49(9), 1642–1648 (2001)

    Article  MATH  Google Scholar 

  39. Y. Yao, H. Vincent Poor, Blind detection of synchronous CDMA in on-Gaussian channels. IEEE Trans. Signal Proc. 52(1), 271–279 (2004)

    Article  Google Scholar 

  40. V. Zarzoso, P. Comon, R. Phlypo, A contrast function for independent component analysis without permutation ambiguity. IEEE Trans. Neural Netw. 21(5), 863–868 (2010)

    Article  Google Scholar 

  41. V. Zarzoso, P. Comon, Optimal step-size constant modulus algorithm. IEEE Trans. Commun. 56(1), 10–13 (2008)

    Article  Google Scholar 

  42. V. Zarzoso, P. Comon, Robust independent component analysis by iterative maximization of the Kurtosis contrast with algebraic optimal step size. IEEE Trans. Neural Netw. 21(2), 248–261 (2010)

    Article  Google Scholar 

  43. V. Zarzoso, P. Comon, Robust independent component analysis, (2009) http://www.i3s.unice.fr/~mh/RR/2009/RR-09.02-V.ZARZOSO.pdf

  44. X.X. Zhang, T.S. Qiu, Blind multiuser detection based on improved Infomax and Fast ICA, in 2nd International Conference on Advanced Computer Control, Shenyang, (2010), pp. 476–479

  45. G. Zhou, Z. Yang, S. Xie, J.M. Yang, Online blind source separation using incremental nonnegative matrix factorization with volume constraint. IEEE Trans. Neural Netw. 22(4), 550–560 (2011)

    Article  MathSciNet  Google Scholar 

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We would like to thank the anonymous reviewers for their helpful comments and evaluation of this paper.

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Correspondence to Zaid Albataineh.

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Albataineh, Z., Salem, F. Robust Blind Multiuser Detection Algorithm Using Fourth-Order Cumulant Matrices. Circuits Syst Signal Process 34, 2577–2595 (2015). https://doi.org/10.1007/s00034-014-9944-9

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