A Non-Stationary Geometry-Based Stochastic Model for MIMO High-Speed Train Channels

In this paper, a non-stationary wideband geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) high-speed train (HST) channels. The proposed model employs multiple confocal ellipses model, where the received signal is a superposition of the line-of-sight (LoS) and single-bounced rays. Because of the time-varying feature of angles of arrival (AoAs), angles of departure (AoDs), and LoS angle, the proposed GBSM has the ability to investigate the non-stationarity of HST environment caused by the high speed movement of the receiver. From the proposed model, the local spatial cross-correlation function (CCF) and the local temporal autocorrelation (ACF) are derived for different taps. Numerical results and analysis show that the proposed channel model is capable of characterizing the time-variant HST wireless channel.