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

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 safet...

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Main Authors: Miaomiao ZHANG, Hao ZHAO, Yan ZHOU, Yang ZHANG, Li YU, Yanping LIANG, Chunjie FENG
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2022-11-01
Series:Dianxin kexue
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Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022043/
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author Miaomiao ZHANG
Hao ZHAO
Yan ZHOU
Yang ZHANG
Li YU
Yanping LIANG
Chunjie FENG
author_facet Miaomiao ZHANG
Hao ZHAO
Yan ZHOU
Yang ZHANG
Li YU
Yanping LIANG
Chunjie FENG
author_sort Miaomiao ZHANG
collection DOAJ
description 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.
format Article
id doaj-art-988bb6f795614f87a23ce436c18538b1
institution Kabale University
issn 1000-0801
language zho
publishDate 2022-11-01
publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-988bb6f795614f87a23ce436c18538b12025-01-15T02:59:56ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012022-11-013815316259575667A long-time & short-time prediction based 5G base station energy-saving policyMiaomiao ZHANGHao ZHAOYan ZHOUYang ZHANGLi YUYanping LIANGChunjie FENGWith 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.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022043/base station energy-savingtraffic predictionintelligent
spellingShingle Miaomiao ZHANG
Hao ZHAO
Yan ZHOU
Yang ZHANG
Li YU
Yanping LIANG
Chunjie FENG
A long-time & short-time prediction based 5G base station energy-saving policy
Dianxin kexue
base station energy-saving
traffic prediction
intelligent
title A long-time & short-time prediction based 5G base station energy-saving policy
title_full A long-time & short-time prediction based 5G base station energy-saving policy
title_fullStr A long-time & short-time prediction based 5G base station energy-saving policy
title_full_unstemmed A long-time & short-time prediction based 5G base station energy-saving policy
title_short A long-time & short-time prediction based 5G base station energy-saving policy
title_sort long time short time prediction based 5g base station energy saving policy
topic base station energy-saving
traffic prediction
intelligent
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022043/
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