An Efficient MIMO Channel Model for LTE-R Network in High-Speed Train Environment

摘要

Long-term evolution for railway (LTE-R) represents a promising network for smart railway, enabling fast and reliable wireless communications on high-speed trains (HSTs) with speeds as high as 500 km/h. To the best of our knowledge, the existing channel models are insufficient to assess such performance. To fill this gap, we propose the tapped delay line model for a 2 x 2 multiple-input multiple-output channel in typical LTE-R HST scenarios. The models are efficient, yet flexible, which can capture the essential channel characteristics in the delay domain, Doppler domain, and spatial domain. Due to the practical difficulties of HST channel measurements, the channel between the fixed transmitter and the high-mobile train cannot be recorded sufficiently for establishing these stochastic models. Therefore, we develop channel models using a ray-tracing (RT) simulator that is validated by HST channel measurements at 2.15 GHz. This paper gives a full parameterization for the proposed channel models, and presents their implementation in channel and link-level simulations. The verification is made through a comparison of the proposed models and the measurement-validated RT simulations in terms of the delay spreads, the eigenvalues, and the error vector magnitudes.