The 5G vehicle-to-everything (V2X) communication for autonomous and semi-autonomous driving utilizes the wireless technology for communication and the Millimeter Wave bands are widely implemented in this kind of vehicular network application. The main purpose of this paper is to broadcast the messages from the mmWave Base Station to vehicles at LOS (Line-of-sight) and NLOS (Non-LOS). Relay using Machine Learning (RML) algorithm is formulated to train the mmBS for identifying the blockages within its coverage area and broadcast the messages to the vehicles at NLOS using a LOS nodes as a relay. The transmission of information is faster with higher throughput and it covers a wider bandwidth which is reused, therefore when performing machine learning within the coverage area of mmBS most of the vehicles in NLOS can be benefited. A unique method of relay mechanism combined with machine learning is proposed to communicate with mobile nodes at NLOS.

本文介绍了一种采用5G车到车（V2X）通信实现的无人驾驶和半自动驾驶技术，利用毫米波技术在通信方面广泛应用于车辆网络应用。文章提出了一种结合机器学习的中继机制来实现基于毫米波基站的广播信息传输，包括通过 LOS节点中继机来将信息传输到 NLOS 的车辆。通过在信号覆盖区域内实现机器学习，实现更快速的信息传输，更广泛的带宽覆盖范围，提高了在 NLOS 区域内车辆的收益。

5G V2X通信中NLOS毫米波的机器学习算法