In 5 G mobile communication systems

millimeter Wave（mmWave） can provide greater bandwidth and higher transmission rates. The mmWave base station can transmit a high gain directional narrow beam through a large-scale antenna array to increase signal coverage. When mmWave base station are densely deployed

users have to search a large number of narrow beams which sent by multiple base stations to find the optimal beam. This process can take a lot of time and computational resources. Therefore

this paper designs a system-level simulation model in a multi-base station scenario

focusing on the layout of users and base stations

large-scale fading

beam-orientation gain

and characteristics of mmWave channels. Finally

a beam search algorithm based on machine learning is designed. Compared with the traditional exhaustive algorithm

this algorithm has lower latency and computational overhead.