  High-mobility adaption and massive Multiple-input Multiple-output (MIMO)
application are two primary evolving objectives for the next generation high
speed train (HST) wireless communication system. In this paper, we consider how
to design a location-aware beamforming for the massive MIMO system in the high
traffic density HST network. We first analyze the tradeoff between beam
directivity and beamwidth, based on which we present the sensitivity analysis
of positioning accuracy. Then, in order to guarantee a high efficient
transmission, we derive an optimal problem to maximize the beam directivity
under the restriction of diverse positioning accuracies. After that, we present
a low-complexity beamforming design by utilizing location information, which
requires neither eigen-decomposing (ED) the uplink channel covariance matrix
(CCM) nor ED the downlink CCM (DCCM). Finally, we study the beamforming scheme
in future high traffic density HST network, where a two HSTs encountering
scenario is emphasized. By utilizing the real-time location information, we
propose an optimal adaptive beamforming scheme to maximize the achievable rate
region under limited channel source constraint. Numerical simulation indicates
that a massive MIMO system with less than a certain positioning error can
guarantee a required performance with satisfying transmission efficiency in the
high traffic density HST scenario and the achievable rate region when two HSTs
encounter is greatly improved as well.
