EM-Based Recursive Estimation of Spatiotemporal Correlation Statistics for Non-stationary MIMO Channel

Yousuke NARUSE  Jun-ichi TAKADA  

IEICE TRANSACTIONS on Communications   Vol.E98-B   No.2   pp.324-334
Publication Date: 2015/02/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E98.B.324
Type of Manuscript: PAPER
Category: Wireless Communication Technologies
MIMO,  channel estimation,  Gauss-Markov model,  Kalman filter,  EM algorithm,  posterior probability,  

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We introduce a MIMO channel estimation method that exploits the channel's spatiotemporal correlation without the aid of a priori channel statistical information. A simplified Gauss-Markov model that has fewer parameters to be estimated is presented for the Kalman filter. In order to obtain statistical parameters on the time evolution of the channel, considering that the time evolution is a latent statistical variable, the expectation-maximization (EM) algorithm is applied for accurate estimation. Numerical simulations reveal that the proposed method is able to enhance estimation capability by exploiting spatiotemporal correlations, and the method works well even if the forgetting factor is small.