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...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2022-08-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022169/ |
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| _version_ | 1841530652167503872 |
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| author | Wei ZHAO Bei LI Ning MENG Tingwei WANG Junfan LIN Le CHEN Yuhua HU Hanyuan YANG |
| author_facet | Wei ZHAO Bei LI Ning MENG Tingwei WANG Junfan LIN Le CHEN Yuhua HU Hanyuan YANG |
| author_sort | Wei ZHAO |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2d0b592800ee47768b5c5d04209783fa |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2022-08-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-2d0b592800ee47768b5c5d04209783fa2025-01-15T03:00:20ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012022-08-013816317059579023Design and implementation of AI-based all-scenario intelligent base station power-saving systemWei ZHAOBei LINing MENGTingwei WANGJunfan LINLe CHENYuhua HUHanyuan YANGIn 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.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022169/base station energy savingSARIMAtraffic prediction5G |
| spellingShingle | Wei ZHAO Bei LI Ning MENG Tingwei WANG Junfan LIN Le CHEN Yuhua HU Hanyuan YANG Design and implementation of AI-based all-scenario intelligent base station power-saving system Dianxin kexue base station energy saving SARIMA traffic prediction 5G |
| title | Design and implementation of AI-based all-scenario intelligent base station power-saving system |
| title_full | Design and implementation of AI-based all-scenario intelligent base station power-saving system |
| title_fullStr | Design and implementation of AI-based all-scenario intelligent base station power-saving system |
| title_full_unstemmed | Design and implementation of AI-based all-scenario intelligent base station power-saving system |
| title_short | Design and implementation of AI-based all-scenario intelligent base station power-saving system |
| title_sort | design and implementation of ai based all scenario intelligent base station power saving system |
| topic | base station energy saving SARIMA traffic prediction 5G |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022169/ |
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