基于AI的全场景智能基站节电系统设计与实现

摘 要：在集约化网络的建设背景下，如何实现自动化、智能化、保体验的基站能耗管理，成为当前运营商的运营管理痛点。创新地提出一种全智能检测、全场景建模、全流程自助的3G/4G/5G智能基站节电方案，通过动态时间规整算法区分覆盖场景，利用SARIMA模型预测时间框构建自适应模型，实时监控指标保证用户感知，自动下发节电策略，短信告警及时拉起。在用户无感知的情况下，实现小区粒度级最大限度节约基站能耗。该方法已在某省网络试点推行，试点区域单站平均节电效率可达9.24%每日，具备实际生产指导意义。

Design and implementation of AI-based all-scenario intelligent base station power-saving system

In the context of intensive network construction, how to realize automatic, intelligent, and experienceguaranteed base station energy consumption management has become a pain point for current operators in operation management.A 3G/4G/5G smart base station power saving solution with full intelligent detection, full-scenario modeling, and full-process self-service was innovatively proposed.The coverage scene was distinguished by a dynamic time warping algorithm, and the SARIMA model was used to predict the time frame to build the model dynamically.Monitoring indicators ensured quality of experience, automatically issue power-saving strategies, and promptly raise SMS alerts.In the case that the user had no perception, the energy consumption of the base station was saved to the greatest extent at the cell granularity level.This method had been implemented on a pilot study in a province.The average annual power saving efficiency of a single station in the pilot area can reach 9.24% per day per station, which can be put in actual production.