Millimeter Wave Beam Tracking Based on Vehicle Environmental Situational Awareness

To address the problem that the previous beam search methods used in the dynamic environment of Telematics cannot solve the problem of real-time matching of millimeter wave narrow beams， this paper proposes a beam search method based on the situational awareness of the vehicle environment in combination with ray tracing method to improve the efficiency of beam search. The method first calculates the optimal beam pair index by ray tracing and encodes the current scene to form a feature vector and build a database； then machine learning is used to train the test vehicle scene to generate a machine learning model for matching the beam of the vehicle network in real situations； Finally a situational search for the actual target vehicle is carried out under the model. The simulation results show that the method can effectively reduce the beam search overhead， improve beam search efficiency while ensuring beam search accuracy.