Mixture Kalman filtering for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels

Ali A. Nasir*, Salman Durrani, Rodney A. Kennedy

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    4 Citations (Scopus)

    Abstract

    This paper proposes a new blind algorithm, based on Mixture Kalman Filtering (MKF), for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels. MKF is a powerful tool for estimating unknown parameters in non-linear, non-Gaussian, real-time applications. We use a combination of Kalman filtering and Sequential Monte Carlo Sampling to estimate the channel fading coefficients and joint posterior probability density of the unknown carrier offset and transmitted data respectively. We study the effect of Signal to Noise Ratio (SNR) and doppler shift on Mean Square Error (MSE) and Bit Error Rate (BER) performance of the proposed algorithm through computer simulations. The results show that BER of the proposed algorithm achieves the theoretical performance slope for the full acquisition range of normalized carrier frequency offset.

    Original languageEnglish
    Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
    Pages3496-3499
    Number of pages4
    DOIs
    Publication statusPublished - 2011
    Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
    Duration: 22 May 201127 May 2011

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    ISSN (Print)1520-6149

    Conference

    Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
    Country/TerritoryCzech Republic
    CityPrague
    Period22/05/1127/05/11

    Fingerprint

    Dive into the research topics of 'Mixture Kalman filtering for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels'. Together they form a unique fingerprint.

    Cite this