The acquisition of the channel covariance matrix is of paramount importance to 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 been proposed in the literature. However, an abrupt change in the channel covariance matrix may happen occasionally in practice due to the change in the scattering environment and the user location. Our paper aims to adopt the classic change detection theory to detect the change in the channel covariance matrix as accurately and quickly as possible such that the new covariance matrix can be re-estimated in time. Specifically, this paper first considers the technique of on-line change detection (also known as quickest/sequential change detection), where we need to detect whether a change in the channel covariance matrix occurs at each channel coherence time interval. Next, because the complexity of detecting the change in a high-dimension covariance matrix at each coherence time interval is too high, we devise a low-complexity off-line strategy in massive MIMO systems, where change detection is merely performed at the last channel coherence time interval of a given time period. Numerical results show that our proposed on-line and off-line schemes can detect the channel covariance change with a small delay and a low false alarm rate. Therefore, our paper theoretically and numerically verifies the feasibility of detecting the channel covariance change accurately and quickly in practice.

翻译：信道协方差矩阵的获取在多输入多输出（MIMO）通信的诸多策略中至关重要，例如最小均方误差（MMSE）信道估计。因此，文献中已提出大量高效的信道协方差矩阵估计方案。然而，在实际场景中，由于散射环境变化和用户位置移动，信道协方差矩阵可能偶尔发生突变。本文旨在采用经典的变化检测理论，尽可能准确且快速地检测信道协方差矩阵的变化，以便及时重新估计新的协方差矩阵。具体而言，本文首先考虑在线变化检测技术（亦称为快速/序贯变化检测），其中需要检测每个信道相干时间间隔内信道协方差矩阵是否发生突变。其次，由于在每个相干时间间隔内检测高维协方差矩阵变化的计算复杂度过高，我们在大规模MIMO系统中设计了一种低复杂度的离线策略，该策略仅在给定时间段内的最后一个信道相干时间间隔执行变化检测。数值结果表明，我们提出的在线与离线方案能够以较小的时延和较低的虚警率检测信道协方差变化。因此，本文从理论和数值上验证了在实际场景中准确且快速检测信道协方差变化的可行性。