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In this paper techniques are proposed for combining information about the mean and the covariance of the channel for the purpose of MIMO transmission. (Partial) Channel State Information at the Transmitter (CSIT) is typically used in MIMO systems for the design of spatial prefiltering and waterfilling. For the purpose of generating CSIT, the cases of mean or covariance information have only been solved separately in the literature. A Bayesian approach is presented here incorporating both pieces of information, but in which correlations are limited to the transmitter side. The approach yields the existing cases of mean or (transmit) covariance information as special instances.
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