Three-three-three network architecture and learning optimization mechanism for B5G/6G
Aiming at the problem that the future B5G/6G network is a complex intelligent network with large connections, coupled with the comprehensive application of 3G, 4G, 5G and even 6G, the future networks will inevitably become extremely complex, a three-three-three network architecture was proposed that...
| Main Authors: | , , |
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| פורמט: | Article |
| שפה: | zho |
| יצא לאור: |
Editorial Department of Journal on Communications
2021-04-01
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| סדרה: | Tongxin xuebao |
| נושאים: | |
| גישה מקוונת: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021095/ |
| _version_ | 1826874857957097472 |
|---|---|
| author | Jinkang ZHU Mingyang CHAI Wuyang ZHOU |
| author_facet | Jinkang ZHU Mingyang CHAI Wuyang ZHOU |
| author_sort | Jinkang ZHU |
| collection | DOAJ |
| description | Aiming at the problem that the future B5G/6G network is a complex intelligent network with large connections, coupled with the comprehensive application of 3G, 4G, 5G and even 6G, the future networks will inevitably become extremely complex, a three-three-three network architecture was proposed that was a network that includes three types of networks (core network, access network and terminal network), three resources (frequency band, power and time consumptions) and three requirements (active, work and service), which was a three-dimensional comprehensive optimization system architecture, referred to as the three-three-three network.Furthermore, the mathematical basic formulas of the three-dimensional complex network were analyzed, the knowledge + data-driven learning model and the optimization method of intelligent processing using the knowledge learning mechanism were presented.Finally, the numerical example and reachable performance of the three-three-three network were given.Those results demonstrate that the proposed network architecture and the learning optimization mechanism are beneficial for designing future large-connected complex intelligent networks. |
| first_indexed | 2025-02-17T00:40:06Z |
| format | Article |
| id | doaj.art-e63642b51a924c3b92c0d23e0a1363b1 |
| institution | Directory Open Access Journal |
| issn | 1000-436X |
| language | zho |
| last_indexed | 2025-02-17T00:40:06Z |
| publishDate | 2021-04-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj.art-e63642b51a924c3b92c0d23e0a1363b12025-01-14T07:21:54ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-04-0142627559741259Three-three-three network architecture and learning optimization mechanism for B5G/6GJinkang ZHUMingyang CHAIWuyang ZHOUAiming at the problem that the future B5G/6G network is a complex intelligent network with large connections, coupled with the comprehensive application of 3G, 4G, 5G and even 6G, the future networks will inevitably become extremely complex, a three-three-three network architecture was proposed that was a network that includes three types of networks (core network, access network and terminal network), three resources (frequency band, power and time consumptions) and three requirements (active, work and service), which was a three-dimensional comprehensive optimization system architecture, referred to as the three-three-three network.Furthermore, the mathematical basic formulas of the three-dimensional complex network were analyzed, the knowledge + data-driven learning model and the optimization method of intelligent processing using the knowledge learning mechanism were presented.Finally, the numerical example and reachable performance of the three-three-three network were given.Those results demonstrate that the proposed network architecture and the learning optimization mechanism are beneficial for designing future large-connected complex intelligent networks.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021095/three-three-three network architectureknowledge learning mechanismknowledge + data driving learning modelreal-time dynamic optimization of complex networklarge connections to complex intelligent network |
| spellingShingle | Jinkang ZHU Mingyang CHAI Wuyang ZHOU Three-three-three network architecture and learning optimization mechanism for B5G/6G Tongxin xuebao three-three-three network architecture knowledge learning mechanism knowledge + data driving learning model real-time dynamic optimization of complex network large connections to complex intelligent network |
| title | Three-three-three network architecture and learning optimization mechanism for B5G/6G |
| title_full | Three-three-three network architecture and learning optimization mechanism for B5G/6G |
| title_fullStr | Three-three-three network architecture and learning optimization mechanism for B5G/6G |
| title_full_unstemmed | Three-three-three network architecture and learning optimization mechanism for B5G/6G |
| title_short | Three-three-three network architecture and learning optimization mechanism for B5G/6G |
| title_sort | three three three network architecture and learning optimization mechanism for b5g 6g |
| topic | three-three-three network architecture knowledge learning mechanism knowledge + data driving learning model real-time dynamic optimization of complex network large connections to complex intelligent network |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021095/ |
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