{"title":"Multi-User Semantic Communications System with Spectrum Scarcity","authors":"Romano Fantacci;Benedetta Picano","doi":"10.23919/JCIN.2022.10005215","DOIUrl":null,"url":null,"abstract":"Nowadays, the emerging paradigm of semantic communications seems to offer an attractive opportunity to improve the transmission reliability and efficiency in new generation communication systems. In particular, focusing on spectrum scarcity, expected to afflict the upcoming sixth generation (6G) networks, this paper analyses the semantic communications behavior in the context of a cell-dense scenario, in which users belonging to different small base station areas may be allocated on a same channel giving rise to a non-negligible interference that severely affects the communications reliability. In such a context, artificial intelligence methodologies are of paramount importance in order to speed up the switch from traditional communication to the novel semantic communication paradigm. As a consequence, a deep-convolution neural networks based encoder-decoder architecture has been exploited here in the definition of the proposed semantic communications framework. Finally, extensive numerical simulations have been performed to test the advantages of the proposed framework in different interfering scenarios and in comparison with different traditional or semantic alternatives.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"7 4","pages":"375-382"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Communications and Information Networks","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10005215/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Nowadays, the emerging paradigm of semantic communications seems to offer an attractive opportunity to improve the transmission reliability and efficiency in new generation communication systems. In particular, focusing on spectrum scarcity, expected to afflict the upcoming sixth generation (6G) networks, this paper analyses the semantic communications behavior in the context of a cell-dense scenario, in which users belonging to different small base station areas may be allocated on a same channel giving rise to a non-negligible interference that severely affects the communications reliability. In such a context, artificial intelligence methodologies are of paramount importance in order to speed up the switch from traditional communication to the novel semantic communication paradigm. As a consequence, a deep-convolution neural networks based encoder-decoder architecture has been exploited here in the definition of the proposed semantic communications framework. Finally, extensive numerical simulations have been performed to test the advantages of the proposed framework in different interfering scenarios and in comparison with different traditional or semantic alternatives.