A long-time ＆ short-time prediction based 5G base station energy-saving policy

Miaomiao ZHANG; Hao ZHAO; Yan ZHOU; Yang ZHANG; Li YU; Yanping LIANG; Chunjie FENG

doi:10.11959/j.issn.1000-0801.2022043

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A long-time ＆ short-time prediction based 5G base station energy-saving policy

Engineering and Application | 更新时间：2024-06-05

- A long-time ＆ short-time prediction based 5G base station energy-saving policy
- Telecommunications Science Vol. 38, Issue 11, Pages: 153-162(2022)
- 作者机构：
  
  1. 中国移动通信有限公司研究院，北京 100053
  2. 中国移动通信集团有限公司，北京 100033
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2022043
  CLC： TN929
- Published Online：2022-11，
  
  Published：20 November 2022
- 稿件说明：
移动端阅览
Miaomiao ZHANG, Hao ZHAO, Yan ZHOU, et al. A long-time ＆ short-time prediction based 5G base station energy-saving policy[J]. Telecommunications science, 2022, 38(11): 153-162.
DOI：

Miaomiao ZHANG, Hao ZHAO, Yan ZHOU, et al. A long-time ＆ short-time prediction based 5G base station energy-saving policy[J]. Telecommunications science, 2022, 38(11): 153-162. DOI： 10.11959/j.issn.1000-0801.2022043.

摘要

随着移动通信技术的发展和5G商用建设的加快，5G功耗将继续大幅度提升运营成本。如何在保障业务体验及设备安全的基础上实现节能最大化，始终是产业界研究的焦点之一。针对网络结构复杂、站型丰富等挑战，提出了以“感知、预测、分析、决策”AI技术为核心的节能策略生成、闭环安全保障技术。基于离线数据，验证了预测技术效果，达到了基站节能误关率低于2%、召回率不低于84%的效果。进一步的实践应用效果证明，在保障网络质量稳定的前提下，能够有效挖掘更多节能空间和节能时长，显著提升节能量，达到降本增效的目的。

Abstract

With the development of the mobile communication technology and the acceleration of 5G commercial network deployment

energy consumption of 5G

which will continue to raise the operating expense significantly.How to maximize the energy efficiency while ensuring service experience and equipment safety has always been one of the research focus in the industry.With the challenges including complexity of network architecture and variety of base station types

an AI-based energy-saving technology including policy generation and closed-loop security assurance of “perception

prediction

analysis

and decision” was introduced.After calibration and validation based on the offline dataset

the false-switch-off rate is less than 2%

and the recall rate is not fewer than 84%.Further study shows that the technology has greater potential on energy-saving.

关键词

Keywords

references

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