On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels |
Lars P. B. Christensen, Jan Larsen
|
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. |
Type | Conference paper [With referee] |
Conference | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Year | 2006 Month May |
Electronic version(s) | [pdf] |
BibTeX data | [bibtex] |
IMM Group(s) | Intelligent Signal Processing |