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

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Abstract

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.

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Acknowledgements

The work was supported in part by National Key R&D Program of China (Grant No. 2018YFB1800800), Basic Research Project of Hetao Shenzhen-HK S&T Cooperation Zone (Grant No. HZQB-KCZYZ-2021067), National Natural Science Foundation of China (Grant Nos. U2001208, 61871137, 62001310), Science and Technology Program of Guangdong Province (Grant No. 2021A0505030002), Shenzhen Fundamental Research Program (Grant No. 20210318123512002), Guangdong Provincial Key Laboratory of Future Networks of Intelligence (Grant No. 2022B1212010001), Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022A1515010109), and Shenzhen Key Laboratory of Big Data and Artificial Intelligence (Grant No. ZDSYS201707251409055).

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Authors and Affiliations

  1. Shenzhen Research Institute of Big Data, Shenzhen, 518172, China

    Guangxu Zhu, Zhonghao Lyu, Xiang Jiao, Peixi Liu & Shuguang Cui

  2. Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen, 518172, China

    Zhonghao Lyu, Jie Xu & Shuguang Cui

  3. School of Science and Engineering (SSE), The Chinese University of Hong Kong (Shenzhen), Shenzhen, 518172, China

    Zhonghao Lyu, Jie Xu & Shuguang Cui

  4. State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, Peking University, Beijing, 100871, China

    Xiang Jiao & Peixi Liu

  5. Department of Electrical and Computer Engineering and Institute for Data Science and Computing, University of Miami, Coral Gables, FL, 33146, USA

    Mingzhe Chen

  6. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Ping Zhang

  7. Peng Cheng Laboratory, Shenzhen, 518066, China

    Shuguang Cui & Ping Zhang

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  1. Guangxu Zhu
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Zhu, G., Lyu, Z., Jiao, X. et al. Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G. Sci. China Inf. Sci. 66, 130301 (2023). https://doi.org/10.1007/s11432-022-3652-2

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