On the error propagation of the fast time varying channel tracking for MIMO system

Channel estimate plays an important role in wireless communications. However, channel tracking has to be considered in the fast time-varying channel. The Bayesian filtering provides an efficient method to capture the dynamics of time varying variables. In this paper, the Bayesian filtering framework is utilized to unveil the error propagation of time-variant channel tracking of MIMO systems. Firstly, the tracking error phenomenon is presented to unveil the influences of uncertainties in dependent factors, e.g., the latest tracking error, measurement error and channel transition uncertainties. Secondly, it is shown that the channel tracking error propagation philosophy is similar to the Ohm's law in circuit theory, which provides intuitive insights into the dominating factors of the time varying channel tracking. Finally, the balance state of channel tracking error propagation is presented to highlight that, the channel tracking precision will gradually converge to a stable value, which depends on the SNR, the channel transition matrix and its transition variance. Finally, numerical results are presented to corroborate the channel tracking error propagation analysis.