基于机器学习的基站覆盖范围仿真

摘要

通过从移动终端上报的经纬度和基站ID, 运用机器学习手段对基站的覆盖范围进行仿真, 并在此基础上对其位置进行优化.避免了基站重复建设所导致的资源浪费, 同时也节省了人工实地测量的高额时间和经济成本, 为高效的网络建设提供了保障.%In this paper, data reported by the mobile terminal, including longitude and latitude, in addition to the ID of the base station are collected. Then machine learning techniques are employed to obtain the simulated coverage of the base stations, hence advoiding the waste of resources in over-construction, at the same time saving the high temporal and financial costs in on-site measuring of parameters, laying a solid foundation for efficient network construction.