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1. 西安电子科技大学人工智能学院,陕西 西安 710071
2. 华中科技大学电子信息与通信学院,湖北 武汉 430074
3. 琶洲实验室,广东 广州 510330
[ "石光明(1965- ),男,博士,西安电子科技大学教授、博士生导师,人工智能学院领军教授,教育部长江学者特聘教授,享受国务院政府特殊津贴专家,IEEE/IET Fellow,中国电子学会会士,人工智能学会高级会员, 2017年以第一完成人荣获国家自然科学奖二等奖1项,主要研究方向为语义通信、类脑感知、压缩感知、计算成像、机器学习、脑电信息处理与脑启发智能技术等" ]
[ "肖泳(1980- ),男,博士,华中科技大学教授,IMT-2030 (6G) 推进组网络智能方向副组长,5G联创行业应用开发实验室副主任,IEEE高级会员,中国通信学会高级会员,IEEE Transactions on Mobile Computing副编辑,主要研究方向为网络人工智能、边缘计算、通信网络博弈理论等" ]
[ "李莹玉(1991- ),女,博士,华中科技大学电子信息与通信学院在站博士后,主要研究方向为物联网、网络大数据分析、分布式优化理论等" ]
[ "高大化(1979- ),男,博士,西安电子科技大学人工智能学院教授、博士生导师,陕西省“青年科技新星”,主持国家重点研发计划、国家自然科学基金等项目10余项,发表智能计算成像相关论文30余篇,授权国际、国内专利10余项,主要研究方向为智能计算成像、智能信息处理等" ]
[ "谢雪梅(1967- ),女,博士,西安电子科技大学人工智能学院教授、博士生导师, IEEE高级会员,入选教育部“新世纪优秀人才支持计划”,获得第十八届中国科协年会全国科技工作者创新创业大赛陕西赛区银奖,在国际期刊和会议上发表了 100多篇学术论文,主要研究方向为人类动作识别、目标检测、场景理解、视频分析、深度学习和特征表示等" ]
纸质出版日期:2021-06-30,
网络出版日期:2021-06,
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石光明, 肖泳, 李莹玉, 等. 面向万物智联的语义通信网络[J]. 物联网学报, 2021,5(2):26-36.
GUANGMING SHI, YONG XIAO, YINGYU LI, et al. Semantic communication networking for the intelligence of everything. [J]. Chinese journal on internet of things, 2021, 5(2): 26-36.
石光明, 肖泳, 李莹玉, 等. 面向万物智联的语义通信网络[J]. 物联网学报, 2021,5(2):26-36. DOI: 10.11959/j.issn.2096-3750.2021.00209.
GUANGMING SHI, YONG XIAO, YINGYU LI, et al. Semantic communication networking for the intelligence of everything. [J]. Chinese journal on internet of things, 2021, 5(2): 26-36. DOI: 10.11959/j.issn.2096-3750.2021.00209.
随着无线通信智能化应用需求的快速提升,未来通信网络将从单纯追求高传输速率的传统架构向面向万物智联的全新架构转变。语义通信是一种可将用户的需求和信息含义融入通信过程中的全新架构,该架构有望成为未来万物智联网络的新型基础范式。介绍了语义通信与万物智联网络的关系及语义通信的基本模型和组成。通过分析点对点语义通信的局限性,提出以知识共享和资源融合为基础的语义通信网络将更适合成为大规模智联网络的基础;通过分析语义通信网络的基本组成,介绍了一种基于联邦边缘智能的语义通信网络范例。仿真结果显示,语义通信网络将有望在保证数据安全的同时,大幅度降低通信的资源需求量并提高通信效率。最后,探讨了语义通信网络未来发展的开放性问题。
With the fast growing demand for the wireless network intelligence
the future communication system will transform from the traditional data-oriented solution to a novel intelligence-of-everything (IoE)-based architecture.Semantic communication is a new communication technology which involves the meaning of message into the communication process.It is believed that semantic communication will have the potential to serve as the fundamental paradigm for the future IoE.The relationship between the semantic communication and IoE was discussed and the basic models and fundamental components of semantic communication were introduced.By discussing the limitations of point-to-point semantic communication
it was argued that the knowledge sharing and resource convergence-based semantic communication networking would be ideal for supporting the future massive scales of IoE systems.The basic components of the semantic communication networking system were discussed and a federated edge intelligence-based semantic communication networking architecture as a case study was considered.Simulation results show that semantic communication networking has the potential to further reduce the resource demand and improve the efficiency of semantic communication.Finally
open problems for future research were discussed.
语义通信万物智联边缘智能联邦学习
semantic communicationintelligence of everythingedge intelligencefederated learning
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