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Empowering the V2X Network by Integrated Sensing and Communications: Background, Design, Advances, and Opportunities
Abstract
To enable next-generation connected autonomous vehicles (CAVs), the future Vehicle-to-everything (V2X) network is expected to provide centimeter-accurate localization service while attaining low-latency transmissions in high-mobility environments. Nevertheless, these unprecedented requirements are far beyond the capabilities of 5G vehicular networks. Given the above evolution trend, a natural idea is thus to design a joint system architecture that combines both communications and sensing subsystems. To this end, research efforts toward integrated sensing and communications (ISAC) for the V2X network are well underway. It is our belief that ISAC should facilitate both sensing and communication via a single system in a spectrum-/energy-/cost-efficient way. Moreover, it can also improve the performance of both functionalities with mutual assistance, which is also essential to enable CAV's mission-critical services for 6G and beyond V2X. In this article, we first provide a brief historical overview of V2X and ISAC. In particular, we analyze the forces driving the usage of ISAC in V2X. Then we introduce three ISAC design schemes based on their underlying systems. We also survey state-of-the-art enabling technologies by reviewing recent developments of ISAC-assisted beamforming technologies in vehicular networks. Finally, we shed light on some potential challenges and research directions.
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“Currently, the NR-V2X sidelink has been standardized by 3GPP to support low-latency high-reliability direct communication.”
From Reinforcement Learning-Based Resource Allocation Scheme of NR-V2X Sidelink for Joint Communication and Sensing (2025) · cites this paper as [24]
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Research works printed but not linked: 15
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- 10.1109/ICASSP.2017.7952790 · DOI
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- 10.1109/JSEN.2015.2458178 · DOI
- 10.1109/TSP.2020.2994394 · DOI
- 10.1109/TWC.2018.2803045 · DOI
- 10.1109/TSP.2018.2847648 · DOI
- 10.1109/MCOM.001.1900700 · DOI
- 10.1109/TVT.2018.2883796 · DOI
- 10.1109/TVT.2020.3006481 · DOI
- 10.1109/TWC.2020.3015735 · DOI
- 10.1109/TWC.2020.3033776 · DOI
Cited by
Sorted by citations
Annu, & Rajalakshmi, P. (2024) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2024.3368240 · Cited by 73
Li, Z., Wang, P., Shen, Y., & Li, S. (2025) · Sensors · doi:10.3390/s25020302 · Cited by 15
Metadata
- Authors
- Zhong, Y., Bi, T., Wang, J., Zeng, J., Huang, Y., Jiang, T., Wu, Q., & Wu, S.
- Affiliations
- Beijing Institute of Technology (CN)
- Chinese Academy of Sciences (CN)
- Beijing University of Posts and Telecommunications (CN)
- University of Technology Sydney (AU)
- Venue
- IEEE Network
- Published
- 2022-07
- Volume
- 36
- Issue
- 4
- Pages
- 54-60
- ISSN
- 0890-8044 (ISSN-L)
- 1558-156X
- OpenAlex
- W4313027809
- Cited by
- 90
- References
- 0
- Citations by year
- 2026: 24 · 2025: 30 · 2024: 22 · 2023: 14
- FWCI
- 4.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Network (publishedVersion)
- Funders
- Beijing Institute of Technology Research Fund Program for Young Scholars
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Keywords
- integrated sensing and communication, vehicle-to-everything networks, connected and autonomous vehicles, vehicular networks, 6G, beamforming, localization, low-latency communication, spectral efficiency, energy efficiency
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