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:获取频道共变矩阵对于多个投入-多输出(MIMO)通信中的许多战略至关重要,例如最小平均方差错误(MMSE)频道估计。因此,文献中提出了大量高效的频道共变矩阵估算办法。然而,由于分散环境和用户位置的变化,频道共变矩阵在实践中可能偶尔发生突变。我们的文件旨在采用典型的变革检测理论,以尽可能准确和快速地检测频道共变矩阵的变化,从而可以及时重新估计新的共变矩阵。具体地说,本文首先考虑了在线变化检测技术(也称为快速/顺序变化检测),我们需要检测频道共变异矩阵是否在每一个频道一致性时间间隔中发生改变。 其次,由于在每一个一致性时间间隔中发现高差异共变矩阵变化的复杂性太高,我们设计了一个低兼容性离线战略,在大规模多变异矩阵中可以重新估算新的共变矩阵矩阵。在大规模MIMIMO系统中,快速的在线检测方法(也称为快速/顺序变化检测 ), 并且只显示我们测算轨道误变变的轨道时间序列测算结果。</s>