C-V2X Link Decision with Machine Learning

Abstract

Vehicle-to-everything (V2X) communications standards have started to reach a maturity in recent years. The evolution period of 5G communications systems also accelerates the development of V2X concept. In this period, cellular V2X (C-V2X) standards are enhanced by the 3GPP organization. In this paper, a novel approach is proposed to decide on a communications link for two different modes (Mode 3 and Mode 4) of C-V2X systems. The proposed approach is developed in an environmental-aware perspective based on machine learning (ML) techniques.