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Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels


An adaptive minimum mean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by (,), into a forgetting factor. For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS) algorithm using the fuzzy-inference-controlled step-size. This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS) and variable forgetting factor RLS (VFF-RLS) algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER) for multipath fading channels.


  1. 1.

    Xie Z, Short RT, Rushforth CK: A family of suboptimum detectors for coherent multiuser communications. IEEE Journal on Selected Areas in Communications 1990, 8(4):683–690. 10.1109/49.54464

    Article  Google Scholar 

  2. 2.

    Widrow B, Mantey PE, Griffiths LJ, Goode BB: Adaptive antenna systems. Proceedings of the IEEE 1967, 55(12):2143–2159.

    Article  Google Scholar 

  3. 3.

    Jim CW: A comparison of two LMS constrained optimal array structures. Proceedings of the IEEE 1977, 65(12):1730–1731.

    Article  Google Scholar 

  4. 4.

    Honig M, Madhow U, Verdú S: Blind adaptive multiuser detection. IEEE Transactions on Information Theory 1995, 41(4):944–960. 10.1109/18.391241

    Article  Google Scholar 

  5. 5.

    Poor HV, Wang X: Code-aided interference suppression for DS/CDMA communications. II. Parallel blind adaptive implementations. IEEE Transactions on Communications 1997, 45(9):1112–1122. 10.1109/26.623076

    Article  Google Scholar 

  6. 6.

    Kecman V: Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models. MIT Press, Cambridge, Mass, USA; 2001.

    Google Scholar 

  7. 7.

    Wu X, Ge L, Liang G: Adaptive power control on the reverse link for CDMA cellular system. Proceedings of 5th IEEE Asia-Pacific Conference on Communications and 4th Optoelectronics and Communications Conference (APCC/OECC '99), October 1999, Beijing, China 1: 608–611.

    Google Scholar 

  8. 8.

    Chang P-R, Wang B-C: Adaptive fuzzy power control for CDMA mobile radio systems. IEEE Transactions on Vehicular Technology 1996, 45(2):225–236. 10.1109/25.492846

    Article  Google Scholar 

  9. 9.

    Chang P-R, Wang B-C: Adaptive fuzzy proportional integral power control for a cellular CDMA system with time delay. IEEE Journal on Selected Areas in Communications 1996, 14(9):1818–1829. 10.1109/49.545704

    Article  Google Scholar 

  10. 10.

    Jamshidi M: Fuzzy logic software and hardware. In Fuzzy Logic and Control: Software and Hardware Applications. Prentice-Hall, Englewood cliffs, NJ, USA; 1993.

    Google Scholar 

  11. 11.

    Gan W-S: Designing a fuzzy step size LMS algorithm. IEE Proceedings - Vision, Image and Signal Processing 1997, 144(5):261–266. 10.1049/ip-vis:19971417

    Article  Google Scholar 

  12. 12.

    Harris RW, Chabries DM, Bishop FA: A variable step (VS) adaptive filter algorithm. IEEE Transactions Acoustics, Speech, Signal Processing 1986, 34(2):309–316. 10.1109/TASSP.1986.1164814

    Article  Google Scholar 

  13. 13.

    Kwong RH, Johnston EW: A variable step size LMS algorithm. IEEE Transactions on Signal Processing 1992, 40(7):1633–1642. 10.1109/78.143435

    Article  Google Scholar 

  14. 14.

    Song S, Lim J-S, Back SJ, Sung K-M: Variable forgetting factor linear least squares algorithm for frequency selective fading channel estimation. IEEE Transactions on Vehicular Technology 2002, 51(3):613–616. 10.1109/TVT.2002.1002509

    Article  Google Scholar 

  15. 15.

    Proakis JG: Digital Communications. 4th edition. McGraw-Hill, New York, NY, USA; 2000.

    Google Scholar 

  16. 16.

    Honig ML, Miller SL, Shensa MJ, Milstein LB: Performance of adaptive linear interference suppression in the presence of dynamic fading. IEEE Transactions on Communications 2001, 49(4):635–645. 10.1109/26.917770

    Article  Google Scholar 

  17. 17.

    Honig ML, Goldstein JS: Adaptive reduced-rank interference suppression based on the multistage Wiener filter. IEEE Transactions on Communications 2002, 50(6):986–994. 10.1109/TCOMM.2002.1010618

    Article  Google Scholar 

  18. 18.

    Rapajic PB, Vucetic BS: Adaptive receiver structures for asynchronous CDMA systems. IEEE Journal on Selected Areas in Communications 1994, 12(4):685–697. 10.1109/49.286675

    Article  Google Scholar 

  19. 19.

    Abdulrahman M, Sheikh AUH, Falconer DD: Decision feedback equalization for CDMA in indoor wireless communications. IEEE Journal on Selected Areas in Communications 1994, 12(4):698–706. 10.1109/49.286676

    Article  Google Scholar 

  20. 20.

    Madhow U, Honig ML: MMSE interference suppression for direct-sequence spread-spectrum CDMA. IEEE Transactions on Communications 1994, 42(12):3178–3188. 10.1109/26.339839

    Article  Google Scholar 

  21. 21.

    Haykin S: Adaptive Filter Theory. 3rd edition. Prentice-Hall, Englewood Cliffs, NJ, USA; 1996.

    Google Scholar 

  22. 22.

    Zadeh LA: Fuzzy sets. Information and Control 1965, 8(3):338–353. 10.1016/S0019-9958(65)90241-X

    MathSciNet  Article  Google Scholar 

  23. 23.

    Chen Y-L, Lin Y-S, Wen J-H, Chang W-M, Liao J: Combined fuzzy-based rate and selective power control in multimedia CDMA cellular systems. Proceedings of 58th IEEE Vehicular Technology Conference (VTC '03), October 2003, Orlando, Fla, USA 4: 2506–2510.

    Google Scholar 

  24. 24.

    Patyra MJ, Grantner JL, Koster K: Digital fuzzy logic controller: design and implementation. IEEE Transactions on Fuzzy Systems 1996, 4(4):439–459. 10.1109/91.544304

    Article  Google Scholar 

  25. 25.

    Costa A, De Gloria A, Faraboschi P, Pagni A, Rizzotto G: Hardware solutions for fuzzy control. Proceedings of IEEE 1995, 83(3):422–434. 10.1109/5.364488

    Article  Google Scholar 

  26. 26.

    Aboulnasr T, Mayyas K: A robust variable step-size LMS-type algorithm: analysis and simulations. IEEE Transactions on Signal Processing 1997, 45(3):631–639. 10.1109/78.558478

    Article  Google Scholar 

  27. 27.

    Lin J, Proakis JG, Ling F, Lev-Ari H: Optimal tracking of time-varying channels: a frequency domain approach for known and new algorithms. IEEE Journal on Selected Areas in Communications 1995, 13(1):141–154. 10.1109/49.363137

    Article  Google Scholar 

  28. 28.

    Jakes WC: Microwave Mobile Communications. John Wiley & Sons, New York, NY, USA; 1974.

    Google Scholar 

  29. 29.

    So CF, Ng SC, Leung SH: Gradient based variable forgetting factor RLS algorithm. Signal Processing 2003, 83(6):1163–1175. 10.1016/S0165-1684(03)00037-9

    Article  Google Scholar 

  30. 30.

    Borah DK, Hart BT: Frequency-selective fading channel estimation with a polynomial time-varying channel model. IEEE Transactions on Communications 1999, 47(6):862–873. 10.1109/26.771343

    Article  Google Scholar 

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Correspondence to Chia-Chang Hu.

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Hu, C., Lin, H., Chen, Y. et al. Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels. EURASIP J. Adv. Signal Process. 2006, 062052 (2006).

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  • Fading Channel
  • Interference Cancellation
  • Multipath Channel
  • Interference Suppression
  • Multipath Fading Channel