On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels

Lars P.B. Christensen, Jan Larsen

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    Abstract

    A general Variational Bayesian framework for iterative data and parameter estimation for coherent detection is introduced as a generalization of the EM-algorithm. Explicit solutions are given for MIMO channel estimation with Gaussian prior and noise covariance estimation with inverse-Wishart prior. Simulation of a GSM-like system provides empirical proof that the VBEM-algorithm is able to provide better performance than the EM-algorithm. However, if the posterior distribution is highly peaked, the VBEM-algorithm approaches the EM-algorithm and the gain disappears. The potential gain is therefore greatest in systems with a small amount of observations compared to the number of parameters to be estimated.
    Original languageEnglish
    Title of host publicationIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    Volume4
    PublisherIEEE
    Publication date2006
    ISBN (Print)1-4244-0469-X
    DOIs
    Publication statusPublished - 2006
    Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing - Toulouse, France
    Duration: 14 May 200619 May 2006
    Conference number: 31

    Conference

    Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing
    Number31
    Country/TerritoryFrance
    CityToulouse
    Period14/05/200619/05/2006

    Bibliographical note

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