Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things (AIoT) in the sixth-generation (6G) era. This gives rise to an emerging research area known as edge inte...

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Bibliographic Details
Published in:Science China. Information sciences 2023-03, Vol.66 (3), p.130301, Article 130301
Main Authors: Zhu, Guangxu, Lyu, Zhonghao, Jiao, Xiang, Liu, Peixi, Chen, Mingzhe, Xu, Jie, Cui, Shuguang, Zhang, Ping
Format: Article
Language:English
Subjects:
Alliances
Artificial intelligence
Cloud computing
Communication
Computer Science
Distillation
Information Systems and Communication Service
Ingredients
Network latency
Pushing
Review
Wireless networks
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Summary:Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things (AIoT) in the sixth-generation (6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication, and computation, which are coupled ingredients for data generation, exchanging, and processing, respectively. However, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation (ISCC) in a task-oriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-022-3652-2