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The acquisition of the channel covariance matrix is of paramount importanceto many strategies in multiple-input-multiple-output (MIMO) communications,such as the minimum mean-square error (MMSE) channel estimation. Therefore,plenty of efficient channel covariance matrix estimation schemes have beenproposed in the literature. However, an abrupt change in the channel covariancematrix may happen occasionally in practice due to the change in the scatteringenvironment and the user location. Our paper aims to adopt the classic changedetection theory to detect the change in the channel covariance matrix asaccurately and quickly as possible such that the new covariance matrix can bere-estimated in time. Specifically, this paper first considers the technique ofon-line change detection (also known as quickest/sequential change detection),where we need to detect whether a change in the channel covariance matrixoccurs at each channel coherence time interval. Next, because the complexity ofdetecting the change in a high-dimension covariance matrix at each coherencetime interval is too high, we devise a low-complexity off-line strategy inmassive MIMO systems, where change detection is merely performed at the lastchannel coherence time interval of a given time period. Numerical results showthat our proposed on-line and off-line schemes can detect the channelcovariance change with a small delay and a low false alarm rate. Therefore, ourpaper theoretically and numerically verifies the feasibility of detecting thechannel covariance change accurately and quickly in practice.

Detecting Abrupt Changes in Channel Covariance Matrix for MIMO Communication