6G知识体系构建：面向全域全场景的学术知识挖掘及其按需应用
6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios
- 通信学报 2023年44卷第9期 页码：173-187
- 作者机构：
西安电子科技大学空天地一体化综合业务网全国重点实验室，陕西 西安710071
- 作者简介：
[ "沙子凡（1998- ），男，江苏扬州人，西安电子科技大学博士生，主要研究方向为6G通信网络、车联网、机器学习技术等" ]
[ "承楠（1987- ），男，辽宁锦州人，博士，西安电子科技大学教授、博士生导师，主要研究方向为智能网联汽车与先进交通系统、无人驾驶、空天地一体化网络技术，人工智能、6G先进网络技术" ]
[ "惠一龙（1988- ），男，陕西西安人，博士，西安电子科技大学博士生导师，主要研究方向为车联网、无人驾驶及数字孪生系统" ]
[ "岳文伟（1992- ），男，山西太原人，博士，西安电子科技大学讲师，主要研究方向为智能交通系统、无线传感器网络、大数据" ]
[ "付宇钏（1992- ），女，陕西汉中人，博士，西安电子科技大学副教授，主要研究方向为车联网、智能驾驶等" ]
[ "孙瑞锦（1992- ），女，山西运城人，博士，西安电子科技大学讲师，主要研究方向为知识驱动的无线网络多维资源按需调度、大规模高动态无人机集群自组织网络" ]
- 基金信息：国家重点研发计划基金资助项目(2020YFB1807700)
DOI：10.11959/j.issn.1000-436x.2023181
中图分类号： TN929.5-
网络首发：2023-09，
纸质出版：2023-09-25
- 稿件说明：
移动端阅览
沙子凡, 承楠, 惠一龙, 等. 6G知识体系构建：面向全域全场景的学术知识挖掘及其按需应用[J]. 通信学报, 2023,44(9):173-187.
Zifan SHA, Nan CHENG, Yilong HUI, et al. 6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios[J]. Journal on Communications, 2023, 44(9): 173-187.
沙子凡, 承楠, 惠一龙, 等. 6G知识体系构建：面向全域全场景的学术知识挖掘及其按需应用[J]. 通信学报, 2023,44(9):173-187. DOI： 10.11959/j.issn.1000-436x.2023181.
Zifan SHA, Nan CHENG, Yilong HUI, et al. 6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios[J]. Journal on Communications, 2023, 44(9): 173-187. DOI： 10.11959/j.issn.1000-436x.2023181.
摘要
当前 6G 相关概念并未统一，亟待一致性的认知和定义，学术和产业界对 6G 的发展全貌和相关领域研究进展缺少清晰认识。为此，构建了 6G 知识库及知识体系。首先，对现有 6G 学术文献进行自动化筛选和结构化存储；其次，在对文本数据进行标注和规范化的基础上构建了6G知识库；再次，利用6G知识库实现了对6G全领域的统计分析；利用自然语言处理、深度神经网络和潜在树模型等技术实现对6G知识的抽取和生成。最后，在大模型训练的基础上，面向多样化的服务需求实现按需的知识应用。
Abstract
At present
the concepts related to 6G have not been unified
and there is an urgent need for consistent cognition and definition.Academics and industries lack a clear understanding of the overall development of 6G and the research progress in related fields.Therefore
the 6G knowledge base and knowledge system was constructed.Firstly
the existing 6G academic documents were automatically screened and stored in a structured way.Secondly
a 6G knowledge base was constructed on the basis of labeling and standardizing text data.In addition
a comprehensive statistical analysis was conducted across all domains of 6G based on the knowledge base and the technologies such as natural language processing
deep neural network and latent tree model were used to realize the extraction and generation of 6G knowledge.Finally
on the basis of large-scale model training
the on-demand knowledge application was realized for diversified service requirements.
关键词
Keywords
references
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