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Electrical Engineering and Systems Science > Signal Processing

arXiv:2205.12073 (eess)
[Submitted on 24 May 2022 (v1), last revised 9 Jul 2022 (this version, v2)]

Title:Edge Semantic Cognitive Intelligence for 6G Networks: Novel Theoretical Models, Enabling Framework, and Typical Applications

Authors:Peihao Dong, Qihui Wu, Xiaofei Zhang, Guoru Ding
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Abstract:Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks, but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated. To this end, this article discusses the concepts of edge intelligence from the semantic cognitive perspective. Two instructive theoretical models for edge semantic cognitive intelligence (ESCI) are first established. Afterwards, the ESCI framework orchestrating deep learning with semantic communication is discussed. Two representative applications are present to shed light on the prospect of ESCI in 6G networks. Some open problems are finally listed to elicit the future research directions of ESCI.
Comments: 9 pages, 7 figures, accepted by China Communications as an invited paper
Subjects: Signal Processing (eess.SP); Information Theory (cs.IT)
Cite as: arXiv:2205.12073 [eess.SP]
  (or arXiv:2205.12073v2 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.2205.12073

Submission history

From: Peihao Dong [view email]
[v1] Tue, 24 May 2022 13:41:54 UTC (484 KB)
[v2] Sat, 9 Jul 2022 06:35:12 UTC (484 KB)
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