SEMANTIC COMMUNICATIONS: A NEW PARADIGM FOR NETWORKED INTELLIGENCE

被引：2

作者：

Zhang, Yimeng ^{[1
]}

Wang, Fengyu ^{[3
]}

Xu, Wenjun ^{[1
,2
]}

Liu, Chenyao ^{[3
]}

机构：

[1] Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Univ Wireless Commun, Beijing 100876, Peoples R China

[2] Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China

[3] Peng Cheng Lab, Shenzhen 518066, Guangdong, Peoples R China

来源：

2022 IEEE 32ND INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP) | 2022年

基金：

中国国家自然科学基金;

关键词：

Networked intelligence; semantic communications; deep learning; 6G;

D O I：

10.1109/MLSP55214.2022.9943480

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Wireless communications are envisioned to shift from "connected things" to "connected/networked intelligence", which is featured by proliferating intelligent objects, intelligent interaction, and autonomous evolution. The resulting massive connections, stringent and variable requirements impose great challenges on 6G to constantly provide optimal service for networked intelligence (NI). We envision semantic communications as a promising roadmap to communications for NI. Specifically, orienting at the interaction intent, semantic communications develop compact representation frameworks, efficient transmission links, and concise network architecture for the networked information interaction and management, enhancing the efficiency, autonomy, intelligence, and scalability of communication systems. In this paper, the key functionalities of semantic-enabled NI and related works are overviewed. Some open issues are discussed at the end.

引用

页数：6

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