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In this paper, we propose a channel tracking method for massive multi-inputand multi-output systems under both time-varying and spatial-varyingcircumstance. Exploiting the characteristics of massive antenna array, aspatial-temporal basis expansion model is designed to reduce the effectivedimensions of up-link and down-link channel, which decomposes channel stateinformation into the time-varying spatial information and gain information. Wefirstly model the users movements as a one-order unknown Markov process, whichis blindly learned by the expectation and maximization (EM) approach. Then, theup-link time varying spatial information can be blindly tracked by Taylorseries expansion of the steering vector, while the rest up-link channel gaininformation can be trained by only a few pilot symbols. Due to anglereciprocity (spatial reciprocity), the spatial information of the down-linkchannel can be immediately obtained from the up-link counterpart, which greatlyreduces the complexity of down-link channel tracking. Various numerical resultsare provided to demonstrate the effectiveness of the proposed method.

Time Varying Channel Tracking with Spatial and Temporal BEM for Massive MIMO Systems