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Combined Equalization and Demodulation of Chaotic Direct Sequence Spread Spectrum Signals for Multipath Channels

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Abstract

Due to the inherent noise-like characteristic of chaotic signals and their sensitivity to the initial value, chaotic direct sequence spread spectrum (CD3S) signals have the advantages of a low probability of intercept (LPI) and a high level of security. Demodulation of non-cooperated CD3S signals is then a challenging issue. If the signal is sent though multipath channels, it is even more difficult for the receiver to demodulate it blindly. Based on the existing theories and methods, we focus more on signals passing through multipath channels. This paper presents an approach to achieve blind equalization and demodulation of CD3S signals through multipath channels. Multiple unscented Kalman filters (UKFs) are used to equalize and demodulate the CD3S signals for the unknown channel. This method can effectively demodulate the signals without any knowledge of the chaotic transmitter’s parameters, initial value, state equation, or the channel coefficients, even when the signal is severely distorted by the multipath channel. Simulation results demonstrate that this method gives faster convergence and better demodulation performance than existing methods for various channel conditions.

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References

  1. S. Azou, C. Pistre, L. Duff, G. Burel, Sea trial results of a chaotic direct sequence spread spectrum under water communication system, in IEEE-OCEANS’03, San Diego, CA (2003)

    Google Scholar 

  2. L. Bai, J. Guo, Breakability of chaotic direct sequence spreading spectrum secure system under multi-path fading channel. Acta Phys. Sin. 60(7), 070504 (2011)

    Google Scholar 

  3. C. Chi, C. Feng, C. Chen, C. Chen, Blind Equalization and System Identification: Batch Processing Algorithm, Performance and Applications (Springer, Berlin, 2006)

    Google Scholar 

  4. K.M. Cuomo, A.V. Oppenheim, S.H. Strogatz, Synchronization of Lorenz-based chaotic circuits with applications to communications. IEEE Trans. Circuits Syst. II 40(10), 626–633 (1993)

    Article  Google Scholar 

  5. H. Dedieu, M.P. Kennedy, M. Hasler, Chaos shift keying: modulation and demodulation of a chaotic carrier using self-synchronizing Chua’s circuits. IEEE Trans. Circuits Syst. II 40(10), 634–642 (1993)

    Article  Google Scholar 

  6. G. Heidari-Bateni, C.D. McGillem, A chaotic direct sequence spread spectrum communication system. IEEE Trans. Commun. 42(2–4), 1524–1527 (1994)

    Article  Google Scholar 

  7. J. Hu, J. Guo, Breaking a chaotic secure communication scheme. Chaos 18, 013121 (2008)

    Article  MathSciNet  Google Scholar 

  8. R. Johnson Jr., P. Schniter, T. Endres, J. Behm, D. Brown, R. Casas, Blind equalization using the constant modulus criterion: a review. Proc. IEEE 86(10), 1927–1950 (1998)

    Article  Google Scholar 

  9. S.J. Julier, J.K. Uhlmann, A new extension of the Kalman filter to nonlinear systems, in Proc. of AeroSense: The 11th Int. Symp. A.D.S.S.C, (1997)

    Google Scholar 

  10. G. Kolumban, M.P. Kennedy, L.O. Chua, The role of synchronization in digital communications using chaos-Part II: chaotic modulation and chaotic synchronization. IEEE Trans. Circuits Syst. I 45(4), 1129–1140 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  11. H. Leung, J. Lam, Design of demodulator for the chaotic modulation communication system. IEEE Trans. Circuits Syst. I 44(3), 262–267 (1997)

    Article  Google Scholar 

  12. H. Leung, H. Yu, K. Murali, Ergodic chaos-based communication schemes. Phys. Rev. E 66(3), 036203 (2002)

    Article  Google Scholar 

  13. M.B. Luca, S. Azou, E. Hodina, Pseudo-blind demodulation of chaotic DSSS signals through exact Kalman filtering, in IEEE Communications Conf., Bucharest, Romania (2006)

    Google Scholar 

  14. K. Murali, H. Leung, H. Yu, Design of noncoherent receiver for analog spread-spectrum communication based on chaotic masking. IEEE Trans. Circuits Syst. I 50(3), 432–441 (2003)

    Article  Google Scholar 

  15. U. Parlitz, S. Ergezinger, Robust communication based on chaotic spreading sequences. Phys. Lett. A 188(2), 146–150 (1994)

    Article  Google Scholar 

  16. L.M. Pecora, T.L. Carroll, Synchronization in chaotic systems. Phys. Rev. Lett. 64(8), 821–824 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  17. D.N. Vizireanu, R.O. Preda, Is “five-point” estimation better than “three-point” estimation? Measurement 46(1), 840–842 (2013)

    Article  Google Scholar 

  18. F. Wang, Z. Wang, J. Guo, Extracting weak harmonic signals from strong chaotic interference. Circuits Syst. Signal Process. 21(4), 427–448 (2002)

    Article  MATH  Google Scholar 

  19. K. Xiong, H. Zhang, C. Chan, Performance evaluation of UKF-based nonlinear filtering. Automatica 42, 261–270 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  20. X. Xu, J. Guo, A novel unified equalization and demodulation of chaotic direct sequence spread spectrum signal based on state estimation. Acta Phys. Sin. 60(2), 020510 (2011)

    Google Scholar 

  21. T. Yang, L. Yang, C. Yang, Breaking chaotic switching using generalized synchronization: examples. IEEE Trans. Circuits Syst. I 45(10), 1062–1067 (1998)

    Article  Google Scholar 

  22. T. Yang, L.O. Chua, Secure communication via chaotic parameter communication. IEEE Trans. Circuits Syst. I 43(9), 817–819 (1996)

    Article  Google Scholar 

  23. H. Zhao, J. Zhang, P. Zeng, Adaptive neural Legendre orthogonal polynomial nonlinear channel equalization for chaos-based communications systems. Acta Phys. Sin. 56(4), 1975–1982 (2007)

    Google Scholar 

  24. H. Zhao, J. Zhang, Adaptive nonlinear channel equalization based on combination neural network for chaos-based communication systems. Acta Phys. Sin. 57(7), 3996–4006 (2008)

    MATH  Google Scholar 

  25. Z. Zhu, H. Leung, Adaptive blind equalization for chaotic communication systems using extended-Kalman filter. IEEE Trans. Circuits Syst. I 48(8), 979–989 (2001)

    Article  Google Scholar 

  26. Z. Zhu, H. Leung, Combined demodulation with adaptive blind-channel equalization for chaotic-modulation communication systems. IEEE Trans. Circuits Syst. I 49(12), 1811–1820 (2002)

    Article  Google Scholar 

  27. Z. Zhu, H. Leung, Channel equalization and timing recovery technique for chaotic communications systems, in ISCAS, Seoul, Korea (2012)

    Google Scholar 

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (Grant No. 51277100) and the State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, China (Grant No. SKLD09M25).

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Correspondence to Jingbo Guo.

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Xu, X., Guo, J. Combined Equalization and Demodulation of Chaotic Direct Sequence Spread Spectrum Signals for Multipath Channels. Circuits Syst Signal Process 32, 2957–2969 (2013). https://doi.org/10.1007/s00034-013-9599-y

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