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In recent years, Over-the-Air Computation (AirComp) has gained significant attention for its ability to ensure data privacy protection and energy efficiency in distributed scenarios. Concurrently, the Perceptive Mobile Vehicle Network (PMVN) has introduced revolutionary advancements in wireless communication through integrated sensing and communication (ISAC). With the convergence of AirComp and PMVN, there are a number of challenges and opportunities that can be utilized to drive technological advancements in artificial intelligence and wireless communication. Motivated by these prospects, this paper investigates the current state of PMVN and AirComp and discusses the open challenges concerning the assistance of AirComp in PMVN. Furthermore, the study identifies existing opportunities in Sensing and Communication (S&C) aided learning, S&C as a task, and edge intelligence. Lastly, the paper explores and analyzes potential future directions. From the perspective of AirComp, this paper offers an overview of PMVN and proposes a framework for sensing­ assisted AirComp in PMVN. We hope this paper will inspire researchers in wireless communication and artificial intelligence.

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Over-the-Air Computation with Integrated Sensing and Communication in Connected Vehicles: Challenges and Future Directions

  • 会议论文

  • 发表日期：

    2025年

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  • Fangning Shi,
  • Quan Zhou,
  • Ronghui Zhang,
  • Yiyang Xiong,
  • Haoming Zhang

摘要

In recent years, Over-the-Air Computation (AirComp) has gained significant attention for its ability to ensure data privacy protection and energy efficiency in distributed scenarios. Concurrently, the Perceptive Mobile Vehicle Network (PMVN) has introduced revolutionary advancements in wireless communication through integrated sensing and communication (ISAC). With the convergence of AirComp and PMVN, there are a number of challenges and opportunities that can be utilized to drive technological advancements in artificial intelligence and wireless communication. Motivated by these prospects, this paper investigates the current state of PMVN and AirComp and discusses the open challenges concerning the assistance of AirComp in PMVN. Furthermore, the study identifies existing opportunities in Sensing and Communication (S&C) aided learning, S&C as a task, and edge intelligence. Lastly, the paper explores and analyzes potential future directions. From the perspective of AirComp, this paper offers an overview of PMVN and proposes a framework for sensing­ assisted AirComp in PMVN. We hope this paper will inspire researchers in wireless communication and artificial intelligence.