6G for Vehicle-to-Everything (V2X) Communications: Enabling Technologies, Challenges, and Opportunities
Open accessAbstract
We are on the cusp of a new era of connected autonomous vehicles with unprecedented user experiences, tremendously improved road safety and air quality, highly diverse transportation environments and use cases, and a plethora of advanced applications. Realizing this grand vision requires a significantly enhanced vehicle-to-everything (V2X) communication network that should be extremely intelligent and capable of concurrently supporting hyperfast, ultrareliable, and low-latency massive information exchange. It is anticipated that the sixth-generation (6G) communication systems will fulfill these requirements of the next-generation V2X. In this article, we outline a series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures. Aiming for truly intelligent transportation systems, we envision that machine learning (ML) will play an instrumental role in advanced vehicular communication and networking. To this end, we provide an overview of the recent advances of ML in 6G vehicular networks. To stimulate future research in this area, we discuss the strength, open challenges, maturity, and enhancing areas of these technologies.
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6G V2X promises revolutionary advancements such as Massive MIMO for higher efficiency and precise beamforming, enhancing overall network performance.
“Now, 6G V2X [6] promises revolutionary advancements such as Massive MIMO for higher efficiency and precise beamforming, enhancing overall network performance.”
From Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed Solutions (2024) · cites this paper as [6]
Cites
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“Adaptive beamforming in a vehicular communication scenario [139] and [140] is possible, but frequent beam training may be needed.”
BackgroundMachine learning for vehicular networks: Recent advances and application examples
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- Authors
- Noor-A-Rahim, M., Liu, Z., Lee, H., Khyam, M. O., He, J., Pesch, D., Moessner, K., Saad, W., & Poor, H. V.
- Affiliations
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
- University of Essex (GB)
- University of Surrey (GB)
- Central Queensland University (AU)
- University College Cork (IE)
- Chemnitz University of Technology (DE)
- Virginia Tech (US)
- Princeton University (US)
- ORCID
- Venue
- Proceedings of the IEEE
- Published
- 2022-06
- Volume
- 110
- Issue
- 6
- Pages
- 712-734
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W3112379500
- Cited by
- 737
- References
- 7
- Citations by year
- 2026: 164 · 2025: 198 · 2024: 193 · 2023: 128 · 2022: 39 · 2021: 15
- FWCI
- 38.21
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the IEEE (publishedVersion, cc-by)
- Open Access at Essex (University of Essex) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- Cork Open Research Archive (University College Cork, Ireland) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- Science Foundation Ireland (16/RC/3918, 13/RC/2077_P2)
- European Union’s Horizon 2020 Research and Innovation Programme under the EDGE CO-FUND Marie Sklodowska Curie (713567)
- EU H2020 Research and Innovation Programme through the 5G-HEART Project (857034)
- DEDICAT 6G Project (101016499)
- European Union’s Horizon 2020 Research and Innovation Programme through the Marie Skodowska-Curie Grant COSAFE (824019)
- Marie Skodowska-Curie Grant VESAFE (101022280)
- U.S. National Science Foundation (CCF-0939370, CNS-1836802, CNS-1814477, CCF-1908308)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- 6G, vehicle-to-everything communication, vehicular networks, autonomous vehicles, intelligent transportation systems, low-latency communication, network architecture
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