Semantic communication networking for the intelligence of everything

Guangming SHI; Yong XIAO; Yingyu LI; Dahua GAO; Xuemei XIE

doi:10.11959/j.issn.2096-3750.2021.00209

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Semantic communication networking for the intelligence of everything

Topic: Edge Intelligence and Fog Computing in IoT | 更新时间：2024-06-05

- Semantic communication networking for the intelligence of everything
- Chinese Journal on Internet of Things Vol. 5, Issue 2, Pages: 26-36(2021)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2021.00209
  CLC： TN929.5
- Published：30 June 2021，
  
  Published Online：2021-06，
- 稿件说明：
移动端阅览
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：

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.

摘要

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。

Abstract

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.

关键词

语义通信万物智联边缘智能联邦学习

Keywords

semantic communicationintelligence of everythingedge intelligencefederated learning

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