Extensible hierarchical codec semantic communication system

被引：0
|
作者：
Zhang Y. [1 ]
Zhao H. [1 ]
Wei J. [1 ]
Cao K. [1 ]
Zhang Y. [1 ]
Luo P. [1 ]
Liu Y. [1 ]
Mei K. [1 ]
机构：
[1] College of Electronic Science and Technology, National University of Defense Technology, Changsha
来源：
Tongxin Xuebao/Journal on Communications | 2023年 / 44卷 / 08期
基金：
中国国家自然科学基金;
关键词：
hierarchical codec; semantic communication; semantic level; syntactic level; verification system;
D O I：
10.11959/j.issn.1000-436x.2023157
中图分类号：
学科分类号：
摘要：
Aiming at the problem that most current researches on text semantic communication mainly rely on simulation system for theoretical verification, an extensible hierarchical semantic communication system was proposed by taking advantage of the separation of hierarchical encoding and decoding architecture in semantic level and grammatical level. The system was compatible with the reliable communication technology under the framework of Shannon information through the mode of semantic and syntactic separation, and realized the nested combination of semantic communication and traditional communication. Furthermore, a universal and extensible verification system was built based on the software radio platform to verify the proposed semantic communication system architecture. The verification system took semantic communication software platform as the driving core of hardware drive and algorithm call, integrated the whole process of signal generation, information transmission, data acquisition, decoding and evaluation at the receiving end, and could be further extended for semantic and syntactic level. Finally, the text semantic communication was tested based on this verification system, which verified that it had higher validity and reliability than the traditional communication mode. © 2023 Editorial Board of Journal on Communications. All rights reserved.
引用
收藏
页码：49 / 60
页数：11
相关论文
共 33 条
  • [1] WEAVER W., Recent contributions to the mathematical theory of communication, ETC: A Review of General Semantics, 10, 4, pp. 261-281, (1953)
  • [2] SHANNON C E., A mathematical theory of communication, The Bell System Technical Journal, 27, 3, pp. 379-423, (1948)
  • [3] SUDAN M., Communication amid uncertainty, Proceedings of 2012 IEEE Information Theory Workshop, pp. 158-161, (2012)
  • [4] SHI G M, LI Y Y, XIE X M., Semantic communications: outcome of the intelligence era, Pattern Recognition and Artificial Intelligence, 31, 1, pp. 91-99, (2018)
  • [5] XU W W, ZHANG G, BAI B, Et al., Ten key ICT challenges in the post-Shannon era, Scientia Sinica (Mathematica), 51, 7, pp. 1095-1138, (2021)
  • [6] ZHANG P, NIU K, TIAN H, Et al., Technology prospect of 6G mobile communications, Journal on Communications, 40, 1, pp. 141-148, (2019)
  • [7] ZHANG Y C, ZHANG P, WEI J B, Et al., Semantic communication for intelligent devices: architectures and a paradigm, Scientia Sinica (Informationis), 52, 5, pp. 907-921, (2022)
  • [8] LIU C H, GUO C L, YANG Y, Et al., Intelligent task-oriented semantic communications: theory, technology and challenges, Journal on Communications, 43, 6, pp. 41-57, (2022)
  • [9] WENG Z Z, QIN Z J, TAO X M, Et al., Deep learning enabled semantic communications with speech recognition and synthesis, IEEE Transactions on Wireless Communications, (2022)
  • [10] SHI G M, XIAO Y, LI Y Y, Et al., Semantic communication networking for the intelligence of everything, Chinese Journal on Internet of Things, 5, 2, pp. 26-36, (2021)
1234