A survey of federated learning for 6G networks
It is an important feature of the 6G that how to realize everything interconnection through large-scale complex heterogeneous networks based on native artificial intelligence (AI).Thanks to the distinct machine learning architecture of data processing locally, federated learning (FL) is regarded as...
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| Format: | Article |
| Language: | zho |
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China InfoCom Media Group
2023-06-01
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| Series: | 物联网学报 |
| Subjects: | |
| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00323/ |
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| _version_ | 1841533795155574784 |
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| author | Guanglei GENG Bo GAO Ke XIONG Pingyi FAN Yang LU Yuwei WANG |
| author_facet | Guanglei GENG Bo GAO Ke XIONG Pingyi FAN Yang LU Yuwei WANG |
| author_sort | Guanglei GENG |
| collection | DOAJ |
| description | It is an important feature of the 6G that how to realize everything interconnection through large-scale complex heterogeneous networks based on native artificial intelligence (AI).Thanks to the distinct machine learning architecture of data processing locally, federated learning (FL) is regarded as one of the promising solutions to incorporate distributed AI in 6G scenarios, and has become a critical research direction of 6G.Therefore, the necessity of introducing distributed AI into the future 6G especially for internet of things (IoT) scenarios was analyzed.And then, the potentials of FL in meeting the 6G requirements were discussed, and the state-of-the-arts of FL related technologies such as architecture design, resource utilization, data transmission, privacy protection, and service provided for 6G were investigated.Finally, several key technical challenges and potential valuable research directions for FL-empowered 6G were put forward. |
| format | Article |
| id | doaj-art-329174b23bc6459fbf76345d74c0c6c8 |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2023-06-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-329174b23bc6459fbf76345d74c0c6c82025-01-15T02:54:31ZzhoChina InfoCom Media Group物联网学报2096-37502023-06-017506659578185A survey of federated learning for 6G networksGuanglei GENGBo GAOKe XIONGPingyi FANYang LUYuwei WANGIt is an important feature of the 6G that how to realize everything interconnection through large-scale complex heterogeneous networks based on native artificial intelligence (AI).Thanks to the distinct machine learning architecture of data processing locally, federated learning (FL) is regarded as one of the promising solutions to incorporate distributed AI in 6G scenarios, and has become a critical research direction of 6G.Therefore, the necessity of introducing distributed AI into the future 6G especially for internet of things (IoT) scenarios was analyzed.And then, the potentials of FL in meeting the 6G requirements were discussed, and the state-of-the-arts of FL related technologies such as architecture design, resource utilization, data transmission, privacy protection, and service provided for 6G were investigated.Finally, several key technical challenges and potential valuable research directions for FL-empowered 6G were put forward.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00323/6G networksinternet of thingsartificial intelligencefederated learning |
| spellingShingle | Guanglei GENG Bo GAO Ke XIONG Pingyi FAN Yang LU Yuwei WANG A survey of federated learning for 6G networks 物联网学报 6G networks internet of things artificial intelligence federated learning |
| title | A survey of federated learning for 6G networks |
| title_full | A survey of federated learning for 6G networks |
| title_fullStr | A survey of federated learning for 6G networks |
| title_full_unstemmed | A survey of federated learning for 6G networks |
| title_short | A survey of federated learning for 6G networks |
| title_sort | survey of federated learning for 6g networks |
| topic | 6G networks internet of things artificial intelligence federated learning |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00323/ |
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