Semantic Communication System Based on Semantic Slice Models Propagation

被引:62
作者
Dong, Chen [1 ]
Liang, Haotai [2 ]
Xu, Xiaodong [1 ,3 ]
Han, Shujun [1 ]
Wang, Bizhu [1 ]
Zhang, Ping [1 ,3 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[3] Peng Cheng Lab, Dept Broadband Commun, Shenzhen 518055, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Semantic communication; models propagation; LSCI; SeSM; SS;
D O I
10.1109/JSAC.2022.3221948
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Traditional communication systems treat messages' semantic aspects and meaning as irrelevant to communication, revealing its limitations in the era of artificial intelligence (AI), such as communication efficiency and intent-sharing among different entities. Through broadening the scope of the traditional communication system and the AI-based encoding techniques, in this manuscript, we present a novel semantic communication system, which involves the essential semantic information exploration, transmission and recovery for more efficient communications. Compared to other state-of-the-art semantic communication-related works, our proposed semantic communication system is characterized by the "flow of the intelligence" via the propagation of the model. Besides, the concept of semantic slice-models (SeSM) is proposed to enable flexible model-resembling under the different requirements of the model performance, channel situation and transmission goals. Specifically, a layer-based semantic communication system for images (LSCI) is built on the simulation platform to demonstrate the feasibility of the proposed system and a novel semantic metric called semantic service quality (SS) is proposed to evaluate the semantic communication systems. We evaluate the proposed system on Cityscapes and Open Images datasets, resulting in averaged 10% and 2% bit rate reduction over JPEG and JPEG2000, respectively. In comparison to LDPC, the proposed channel coding scheme can averagely save 2dB and 5dB in AWGN channel and Rayleigh fading channel, respectively.
引用
收藏
页码:202 / 213
页数:12
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