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Article: A Unified Framework for Integrating Semantic Communication and AI-Generated Content in Metaverse

TitleA Unified Framework for Integrating Semantic Communication and AI-Generated Content in Metaverse
Authors
KeywordsAIGC
Diffusion
Metaverse
Resource Allocation
Semantic Communication
Issue Date2024
Citation
IEEE Network, 2024, v. 38, n. 4, p. 174-181 How to Cite?
AbstractAs the Metaverse continues to grow, the need for efficient communication and intelligent content generation becomes increasingly important. Semantic communication focuses on conveying meaning and understanding from user inputs, while AI-Generated Content utilizes artificial intelligence to create digital content and experiences. Integrated Semantic Communication and AI-Generated Content (ISGC) has attracted a lot of attentions recently, which transfers semantic information from user inputs instead of raw data, generates digital content, and renders graphics for Metaverse. In this paper, we introduce a unified framework that captures ISGC's two primary benefits: integration gain for optimized resource allocation and coordination gain for goal-oriented high-quality content generation to improve immersion from both communication and content perspectives. We also classify existing ISGC solutions, analyze the major components of ISGC, and present several use cases. We then construct a case study based on the diffusion model to identify a near-optimal resource allocation strategy for performing semantic extraction, content generation, and graphic rendering in the Metaverse. Finally, we discuss several open research issues, encouraging further exploring the potential of ISGC and its related applications in the Metaverse.
Persistent Identifierhttp://hdl.handle.net/10722/353116
ISSN
2023 Impact Factor: 6.8
2023 SCImago Journal Rankings: 3.896

 

DC FieldValueLanguage
dc.contributor.authorLin, Yijing-
dc.contributor.authorGao, Zhipeng-
dc.contributor.authorDu, Hongyang-
dc.contributor.authorNiyato, Dusit-
dc.contributor.authorKang, Jiawen-
dc.contributor.authorJamalipour, Abbas-
dc.contributor.authorShen, Xuemin Sherman-
dc.date.accessioned2025-01-13T03:02:10Z-
dc.date.available2025-01-13T03:02:10Z-
dc.date.issued2024-
dc.identifier.citationIEEE Network, 2024, v. 38, n. 4, p. 174-181-
dc.identifier.issn0890-8044-
dc.identifier.urihttp://hdl.handle.net/10722/353116-
dc.description.abstractAs the Metaverse continues to grow, the need for efficient communication and intelligent content generation becomes increasingly important. Semantic communication focuses on conveying meaning and understanding from user inputs, while AI-Generated Content utilizes artificial intelligence to create digital content and experiences. Integrated Semantic Communication and AI-Generated Content (ISGC) has attracted a lot of attentions recently, which transfers semantic information from user inputs instead of raw data, generates digital content, and renders graphics for Metaverse. In this paper, we introduce a unified framework that captures ISGC's two primary benefits: integration gain for optimized resource allocation and coordination gain for goal-oriented high-quality content generation to improve immersion from both communication and content perspectives. We also classify existing ISGC solutions, analyze the major components of ISGC, and present several use cases. We then construct a case study based on the diffusion model to identify a near-optimal resource allocation strategy for performing semantic extraction, content generation, and graphic rendering in the Metaverse. Finally, we discuss several open research issues, encouraging further exploring the potential of ISGC and its related applications in the Metaverse.-
dc.languageeng-
dc.relation.ispartofIEEE Network-
dc.subjectAIGC-
dc.subjectDiffusion-
dc.subjectMetaverse-
dc.subjectResource Allocation-
dc.subjectSemantic Communication-
dc.titleA Unified Framework for Integrating Semantic Communication and AI-Generated Content in Metaverse-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/MNET.2023.3321539-
dc.identifier.scopuseid_2-s2.0-85174803388-
dc.identifier.volume38-
dc.identifier.issue4-
dc.identifier.spage174-
dc.identifier.epage181-
dc.identifier.eissn1558-156X-

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