Extended Context-Based Semantic Communication System for Text Transmission

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aut.relation.endpage576
aut.relation.issue3
aut.relation.journalDigital Communications and Networks
aut.relation.startpage568
aut.relation.volume10
dc.contributor.authorLiu, Yueling
dc.contributor.authorJiang, Shengteng
dc.contributor.authorZhang, Yichi
dc.contributor.authorCao, Kuo
dc.contributor.authorZhou, Li
dc.contributor.authorSeet, Boon-Chong
dc.contributor.authorZhao, Haitao
dc.contributor.authorWei, Jibo
dc.date.accessioned2024-09-05T22:59:50Z
dc.date.available2024-09-05T22:59:50Z
dc.date.issued2022-10-08
dc.description.abstractContext information is significant for semantic extraction and recovery of messages in semantic communication. However, context information is not fully utilized in the existing semantic communication systems since relationships between sentences are often ignored. In this paper, we propose an Extended Context-based Semantic Communication (ECSC) system for text transmission, in which context information within and between sentences is explored for semantic representation and recovery. At the encoder, self-attention and segment-level relative attention are used to extract context information within and between sentences, respectively. In addition, a gate mechanism is adopted at the encoder to incorporate the context information from different ranges. At the decoder, Transformer-XL is introduced to obtain more semantic information from the historical communication processes for semantic recovery. Simulation results show the effectiveness of our proposed model in improving the semantic accuracy between transmitted and recovered messages under various channel conditions.
dc.identifier.citationDigital Communications and Networks, ISSN: 2352-8648 (Print); 2352-8648 (Online), Elsevier BV, 10(3), 568-576. doi: 10.1016/j.dcan.2022.09.023
dc.identifier.doi10.1016/j.dcan.2022.09.023
dc.identifier.issn2352-8648
dc.identifier.issn2352-8648
dc.identifier.urihttp://hdl.handle.net/10292/17982
dc.languageen
dc.publisherElsevier BV
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S2352864822001985
dc.rights© 2022 Chongqing University of Posts and Telecommunications. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject4605 Data Management and Data Science
dc.subject46 Information and Computing Sciences
dc.subject40 Engineering
dc.subject0805 Distributed Computing
dc.subject1005 Communications Technologies
dc.subject1203 Design Practice and Management
dc.subject4006 Communications engineering
dc.subject4606 Distributed computing and systems software
dc.titleExtended Context-Based Semantic Communication System for Text Transmission
dc.typeJournal Article
pubs.elements-id480672
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