Proc. IEEE Global Communications Conference,
Nov. 27-Dec 1, 2006, accepted for publication.
Exploiting Spatio-Temporal Correlations in
MIMO Wireless Channel Prediction
Ian C. Wong and
Brian L. Evans
Department of Electrical and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712-1084 USA
Paper Draft -
OFDM Research at UT Austin
We investigate prediction algorithms that exploit both temporal
and spatial correlations in MIMO correlated narrowband fading
We first derive the optimal two dimensional minimum mean square
error (2D-MMSE) prediction filter that maximally exploits the
available temporal and spatial correlations.
We then propose a lower complexity 2-step prediction algorithm,
which first exploits temporal correlations using a classical
single-input single-output MMSE (SISO-MMSE) time domain prediction
filter for each entry in the MIMO channel, followed by an MMSE
spatial smoothing step to exploit the spatial correlations.
Compared to the SISO-MMSE and specular prediction approaches,
this approach either achieves lower MSE with a slight increase in
complexity, or comparable MSE with lower complexity, in a wide
range of wireless channel conditions.
The same advantage holds for the average mutual information.
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Last Updated 07/21/06.