@CONFERENCE\{IMM2006-04415,
    author       = "L. P. B. Christensen and J. Larsen",
    title        = "On Data and Parameter Estimation Using the Variational Bayesian {EM-}algorithm for Block-fading Frequency-selective {MIMO} Channels",
    year         = "2006",
    month        = "may",
    booktitle    = "{IEEE} International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/4415-full.html",
    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."
}