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Breaking Chaotic Direct Sequence Spreading Spectrum Signals Under the Multipath Fading Channel

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Abstract

In order to break chaotic direct sequence spreading spectrum (CD3S) signals under the multipath fading channel, a particle filter based algorithm combining blind channel equalization with chaos fitting is proposed. To implement this algorithm, the intruder substitutes a different chaotic equation into the state-space equations of the channel and the chaos fitting, and then multiple particle filters are used for blind channel equalization and chaos fitting simultaneously by implementing them in reciprocal interaction. As a result, the impact brought about by the multipath fading channel and additive noises can be overcome. Furthermore, the range-differentiating factor is used to make the inevitable chaos fitting error advantageous based on the chaos fitting method. Thus, the CD3S signals can be broken according to the range of the estimated message. Simulations show that the binary message signal can be extracted from the CD3S signals without any knowledge of the chaotic transmitter’s structure, parameters, initial value, or the channel characteristics.

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References

  1. V. Afeaimovich, A. Cordonet, N.F. Rulkov, Generalized synchronization of chaos in noninvertible maps. Phys. Rev. E 66, 016208 (2002)

    Article  MathSciNet  Google Scholar 

  2. G. Alvarez, F. Montoya, M. Romera, G. Pastor, Breaking two secure communication systems based on chaotic masking. IEEE Trans. Circuits Syst. II, Express Briefs 51(10), 505–506 (2004)

    Article  Google Scholar 

  3. G. Alvarez, F. Montoya, M. Romera, G. Pastor, Breaking parameter modulated chaotic secure communication system. Chaos Solitons Fractals 21(4), 783–787 (2004)

    Article  MATH  Google Scholar 

  4. M.S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Signal Process. 50(2), 174–188 (2002)

    Article  Google Scholar 

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

    Google Scholar 

  6. K.M. Cuomo, A.V. Oppenheim, Chaotic signals and systems for communications, in Proc. of IEEE ICASSP, vol. 3 (1993), pp. 137–140

    Google Scholar 

  7. Y. Fu, H. Leung, Narrowband interference cancellation in spread spectrum communication systems using chaos. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl. 48, 847–858 (2001)

    Article  Google Scholar 

  8. N.J. Gordon, D.J. Salmond, A.F.M. Smith, Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proc., F, Radar Signal Process. 140(2), 107–113 (1993)

    Article  Google Scholar 

  9. Z.H. Hu, J.C. Feng, Blind channel equalization algorithm based on dual unscented Kalman filter for chaotic multi-input multi-output communication systems. Trans. Tianjin Univ. 18, 33–37 (2012)

    Article  Google Scholar 

  10. J.F. Hu, J.B. Guo, Breaking a chaotic direct sequence spreading spectrum secure communication system. Acta Phys. Sin. 57(3), 1477–1484 (2008)

    MATH  MathSciNet  Google Scholar 

  11. Y. Hwang, H.C. Papadopoulos, Physical-layer secrecy in AWGN via a class of chaotic DS/SS systems: analysis and design. IEEE Trans. Signal Process. 52(9), 2637–2649 (2004)

    Article  Google Scholar 

  12. S.J. Julier, J.K. Uhlmann, H.D. Whyte, A new approach for filtering nonlinear systems, in American Control Conf., vol. 3 (1995), pp. 1628–1632

    Google Scholar 

  13. N.P. Michail, E.G. Alivizatos, N.K. Uzunoglu, Manoeuvring target tracking using multiple bistatic range and range-rate measurement. Signal Process. 87, 665–686 (2007)

    Article  MATH  Google Scholar 

  14. E. Punskaya, C. Andrieu, A. Doucet, W.J. Fitzgerald, Particle filtering for demodulation in fading channels with non-Gaussian additive noise. IEEE Trans. Commun. 49(4), 579–582 (2001)

    Article  MATH  Google Scholar 

  15. N. Sharma, E. Ott, Combating channel distortions in communication with chaotic systems. Phys. Lett. A 248, 347–352 (1998)

    Article  Google Scholar 

  16. R.D. Van Merwe, E.A. Wan, S.I. Julier, Sigma-point Kalman filters for nonlinear estimation and sensor-fusion applications to integrated navigation, in AIAA Guidance, Navigation, and Control Conf., vol. 3 (2004), pp. 1735–1764

    Google Scholar 

  17. C. Vural, G. Cetinel, Blind equalization of single-input FIR channels for chaotic communication systems. Digit. Signal Process. 20, 201–211 (2010)

    Article  Google Scholar 

  18. B.Y. Wang, C.W.S. Tommy, K.T. Ng, Blind adaptive identification of FIR channel in chaotic communication systems. Chin. Phys. 13, 329–334 (2004)

    Article  Google Scholar 

  19. N. Xie, H. Leung, Blind equalization using a predictive radial basis function neural network. IEEE Trans. Neural Netw. 16(3), 709–719 (2005)

    Article  Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  22. J.S. Zhang, Robust blind adaptive channel equalization in chaotic communication systems. Chin. Phys. Lett. 23(12), 3187–3189 (2006)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Instrument Science and Technology, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan Province, 410073, P.R. China

    Ting Li, Dexin Zhao, Zhiping Huang, Shaojing Su, Chunwu Liu & Zhen Zuo

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  1. Ting Li
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  2. Dexin Zhao
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  3. Zhiping Huang
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  4. Shaojing Su
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  5. Chunwu Liu
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  6. Zhen Zuo
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Correspondence to Ting Li.

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Li, T., Zhao, D., Huang, Z. et al. Breaking Chaotic Direct Sequence Spreading Spectrum Signals Under the Multipath Fading Channel. Circuits Syst Signal Process 33, 973–986 (2014). https://doi.org/10.1007/s00034-013-9666-4

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  • DOI: https://doi.org/10.1007/s00034-013-9666-4

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