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1. 中国联合网络通信有限公司浙江省分公司,浙江 杭州 310051
2. 中国联合网络通信有限公司研究院,北京 100048
3. 中国联合网络通信集团有限公司,北京 100033
[ "赵伟(1982- ),男,中国联合网络通信有限公司浙江省分公司工程师,主要研究方向为网络优化、大数据及人工智能在移动通信中的应用" ]
[ "李贝(1983- ),女,中国联合网络通信有限公司研究院高级工程师,主要研究方向为网络智能运营" ]
[ "孟宁(1979- ),男,中国联合网络通信集团有限公司高级工程师,主要研究方向为重点场景专项优化" ]
[ "王廷伟(1985- ),男,中国联合网络通信有限公司浙江省分公司工程师,主要研究方向为移网网络规划和优化,以及数字化前沿技术在移动通信中的应用" ]
[ "林俊钒(1996- ),男,中国联合网络通信有限公司浙江省分公司高级工程师,主要研究方向为大数据及人工智能在移动通信中的创新应用" ]
[ "陈乐(1992- ),女,中国联合网络通信有限公司浙江省分公司高级工程师,主要研究方向为大数据及人工智能在移动通信中的应用" ]
[ "胡煜华(1973- ),男,中国联合网络通信有限公司浙江省分公司高级工程师,主要研究方向为无线网络规划建设优化" ]
[ "杨汉源(1985- ),男,中国联合网络通信有限公司浙江省分公司工程师,主要研究方向为无线网络优化" ]
网络出版日期:2022-08,
纸质出版日期:2022-08-20
移动端阅览
赵伟, 李贝, 孟宁, 等. 基于AI的全场景智能基站节电系统设计与实现[J]. 电信科学, 2022,38(8):163-170.
Wei ZHAO, Bei LI, Ning MENG, et al. Design and implementation of AI-based all-scenario intelligent base station power-saving system[J]. Telecommunications science, 2022, 38(8): 163-170.
赵伟, 李贝, 孟宁, 等. 基于AI的全场景智能基站节电系统设计与实现[J]. 电信科学, 2022,38(8):163-170. DOI: 10.11959/j.issn.1000-0801.2022169.
Wei ZHAO, Bei LI, Ning MENG, et al. Design and implementation of AI-based all-scenario intelligent base station power-saving system[J]. Telecommunications science, 2022, 38(8): 163-170. DOI: 10.11959/j.issn.1000-0801.2022169.
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。
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.
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