The decision-directed space-alternating generalized expectation-maximization (SAGE) algorithm is introduced in [1] to estimate the channel and track the channel varying for OFDM systems with transmitter diversity. However, this method is based upon a discrete Fourier transform (DFT), which will cause power leakage and result in an error floor in a multipath channel with non-sample-spaced time delays. In order to overcome this problem, a low rank approximation method is presented by using the signal subspace of the channel frequency autocorrelation matrix. Furthermore, a modified fast subspace tracking algorithm is introduced to adaptive estimate the signal subspace by using a space–time block coded training blocks sent at regular interval. Simulation results show the advantages of the proposed technique for MIMO-OFDM systems in time-varying non-sample-spaced wireless channels.


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    Title :

    Channel Estimation for MIMO-OFDM Systems in Non-sample-Spaced Multipath Channels


    Contributors:
    Wu, Yun (author) / Luo, Hanwen (author)


    Publication date :

    2008-05-01


    Size :

    481508 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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