Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network
Load balancing is a huge challenge for LTE multi-frequency and multi-mode network.Hundreds of parameters are involved in load balancing for the complex network structure.Therefore,it is difficult to perform precise and meticulous configuration only relying on human experience.In order to cope with t...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2020-07-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020159/ |
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| author | Yaxing QIU Xidong WANG Sen BIAN Lei YUE |
| author_facet | Yaxing QIU Xidong WANG Sen BIAN Lei YUE |
| author_sort | Yaxing QIU |
| collection | DOAJ |
| description | Load balancing is a huge challenge for LTE multi-frequency and multi-mode network.Hundreds of parameters are involved in load balancing for the complex network structure.Therefore,it is difficult to perform precise and meticulous configuration only relying on human experience.In order to cope with the challenge,a load balancing scheme based on clustering analysis and deep learning was proposed.Firstly,the key indicators were selected to identify the network scenes,and then big data and deep learning technologies were used to mine the relationship between data.Finally,the optimum system parameters for different network scenes were found.It has been proved that machine learning technology can greatly improve the accuracy and the efficiency of parameter configuration. |
| format | Article |
| id | doaj-art-37c7c59676574c7dac5b9ec062f0b37c |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2020-07-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-37c7c59676574c7dac5b9ec062f0b37c2025-01-15T03:00:29ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012020-07-013615616259582374Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode networkYaxing QIUXidong WANGSen BIANLei YUELoad balancing is a huge challenge for LTE multi-frequency and multi-mode network.Hundreds of parameters are involved in load balancing for the complex network structure.Therefore,it is difficult to perform precise and meticulous configuration only relying on human experience.In order to cope with the challenge,a load balancing scheme based on clustering analysis and deep learning was proposed.Firstly,the key indicators were selected to identify the network scenes,and then big data and deep learning technologies were used to mine the relationship between data.Finally,the optimum system parameters for different network scenes were found.It has been proved that machine learning technology can greatly improve the accuracy and the efficiency of parameter configuration.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020159/multi-frequency and multi-mode networkmachine learningload optimization |
| spellingShingle | Yaxing QIU Xidong WANG Sen BIAN Lei YUE Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network Dianxin kexue multi-frequency and multi-mode network machine learning load optimization |
| title | Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network |
| title_full | Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network |
| title_fullStr | Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network |
| title_full_unstemmed | Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network |
| title_short | Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network |
| title_sort | load balancing based on clustering analysis and deep learning for multi frequency and multi mode network |
| topic | multi-frequency and multi-mode network machine learning load optimization |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020159/ |
| work_keys_str_mv | AT yaxingqiu loadbalancingbasedonclusteringanalysisanddeeplearningformultifrequencyandmultimodenetwork AT xidongwang loadbalancingbasedonclusteringanalysisanddeeplearningformultifrequencyandmultimodenetwork AT senbian loadbalancingbasedonclusteringanalysisanddeeplearningformultifrequencyandmultimodenetwork AT leiyue loadbalancingbasedonclusteringanalysisanddeeplearningformultifrequencyandmultimodenetwork |