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

Lars P. B. Christensen, Jan Larsen

AbstractA 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.
TypeConference paper [With referee]
ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year2006    Month May
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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