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Cross-Coupled Rao-Blackwellized Particle and Kalman Filters for the Joint Symbol-Channel Estimation in MC-DS-CDMA Systems

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Part of the book series: Lecture Notes Electrical Engineering ((LNEE,volume 1))

Abstract

This paper deals with the joint symbol-channel estimation for quasi-synchronous Multi-carrier Direct-Sequence Code DivisionMultiple Access (MC-DS-CDMA) systems over Rayleigh fading channels. To solve this non-linear problem, Rao- Blackwellized particle filters have proved efficient. In this framework, our contribution is twofold. 1) Instead of using an autoregressive (AR) model which does not match the bandlimitation of the theoretical power spectrum density (PSD) of a Rayleigh channel, we suggest modeling the channel by a low-pass filtered version of the so-called stochastic sinusoidal process. It consists of sinusoids in quadrature with random magnitudes modeled as AR processes. By suitably choosing the AR parameters, this combination has the advantage of providing a stationnary process whose PSD is bandlimited and has two peaks at the maximum Doppler frequency for any AR order. 2) The estimation of the model parameters is included in the joint symbol-channel estimation process. For this purpose, a deterministic Rao-Blackewellized Particle Filter which jointly estimates the symbols and the channels is cross-coupled with a Kalman Filter which yields the AR parameters.

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References

  1. W. C. Jakes, “Microwave Mobile Communications”, Wiley-Interscience, New-year, 1974.

    Google Scholar 

  2. Z. Chen, “Bayesian Filtering: from Kalman Filters to Particle Filters, and Beyond”, http://users.isr.ist.utl.pt/jpg/tfc0607/chen_bayesian.pdf, Canada, 2003.

    Google Scholar 

  3. B. D. O. Anderson and J. B. Moore, “Optimal Filtering”, Prentice-Hall, New Jersey, 1979.

    MATH  Google Scholar 

  4. K. E. Baddour and N. C. Beaulieu, “Autoregressive Modeling for Fading Channel Simulation”, IEEE Trans. On Wireless Commun., vol. 4, pp. 1650-1662, July 2005.

    Article  Google Scholar 

  5. P. Y. Kam, “Optimal Detection of Digital Data over the Nonselective Rayleigh Fading Channel with Diversity Reception”, IEEE Trans. on Commun., vol. 39, pp. 214-219, Feb. 1991.

    Article  Google Scholar 

  6. Y. Liu and S. D. Blostein, “Identification of Frequency Nonselective Fading Channels using Decision Feedback and Adaptive Linear Prediction”, IEEE Trans. on Commun., vol. 43, pp. 1484-1492, Feb. 1995.

    Article  Google Scholar 

  7. R. Raheli, A. Polydoros and C. Tzou, “Per-survivor Processing: a general approach to MLSE in uncertain environments”, IEEE Trans. on Commun., vol. 43, pp. 1354-364, Feb. 1995.

    Article  Google Scholar 

  8. E. Punskaya, “Sequential Monte Carlo Methods for Digital Communications“, Ph.D. thesis, University of Cambridge, 2003.

    Google Scholar 

  9. E. Punskaya, A. Doucet and W. J. Fitzgerald, “Particle Filtering for Joint Symbol and Parameter Estimation in DS Spread Spectrum Systems”, Proceedings of ICASSP, Hong Kong, Apr. 2003.

    Google Scholar 

  10. X. Wang, R. Chen, and D. Guo, “Delayed-Pilot Sampling for Mixture Kalman Filter with Application in Fading Channels“, IEEE Trans. on Sig. Proc., vol.50, no. 2, Feb. 2002.

    Google Scholar 

  11. Y. Huang, J. Zhang, I. T. Luna, P. M. Djuric and D. P. R. Padillo, “Adaptive Blind Multiuser Detection over Flat Fast Fading Channels using Particle Filtering”, Proceeding of Globecom, 2004.

    Google Scholar 

  12. H. Wu and A. Duel-Hallen, “Multiuser Detectors with Disjoint Kalman Channel Estimators for Synchronous CDMA Mobile Radio Channels”, IEEE Trans. on Commun. vol. 48, no. 5, May 2000.

    Google Scholar 

  13. A. Papoulis, “Predictable Processes and Wold’s Decomposition: a Review”, IEEE Trans. on Acous. Speech and Signal Proc., vol. ASSP-33, no. 4, Aug. 1985.

    Google Scholar 

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Grolleau, J., Giremus, A., Grivel, E. (2007). Cross-Coupled Rao-Blackwellized Particle and Kalman Filters for the Joint Symbol-Channel Estimation in MC-DS-CDMA Systems. In: Plass, S., Dammann, A., Kaiser, S., Fazel, K. (eds) Multi-Carrier Spread Spectrum 2007. Lecture Notes Electrical Engineering, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6129-5_42

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  • DOI: https://doi.org/10.1007/978-1-4020-6129-5_42

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-6128-8

  • Online ISBN: 978-1-4020-6129-5

  • eBook Packages: EngineeringEngineering (R0)

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