6G for vehicle-to-everything (V2X) communications: Enabling technologies, challenges, and opportunities
dc.contributor.author | Noor-A-Rahim, Md. | |
dc.contributor.author | Liu, Zilong | |
dc.contributor.author | Lee, Haeyoung | |
dc.contributor.author | Khyam, Mohammad Omar | |
dc.contributor.author | He, Jianhua | |
dc.contributor.author | Pesch, Dirk | |
dc.contributor.author | Moessner, Klaus | |
dc.contributor.author | Saad, Walid | |
dc.contributor.author | Poor, H.Vincent | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.contributor.funder | Horizon 2020 | en |
dc.contributor.funder | HORIZON EUROPE Marie Sklodowska-Curie Actions | en |
dc.contributor.funder | National Science Foundation | en |
dc.date.accessioned | 2022-09-28T14:16:56Z | |
dc.date.available | 2022-09-28T14:16:56Z | |
dc.date.issued | 2022-05-20 | |
dc.date.updated | 2022-09-28T14:04:09Z | |
dc.description.abstract | 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. | en |
dc.description.sponsorship | Science Foundation Ireland (under Grant 16/RC/3918 (Confirm Centre for Smart Manufacturing) and Grant 13/RC/2077_P2 (CONNECT: The Centre for Future Networks & Communications); European Union’s Horizon 2020 Research and Innovation Programme under the EDGE CO-FUND Marie Sklodowska Curie Grant 713567; in part by the EU H2020 Research and Innovation Programme through the 5G-HEART Project under Grant Agreement 857034 and the DEDICAT 6G Project under Grant Agreement 101016499; in part by the European Union’s Horizon 2020 Research and Innovation Programme through the Marie Skodowska-Curie Grant COSAFE under Agreement 824019 and the Marie Skodowska-Curie Grant VESAFE under Agreement 101022280) U.S. National Science Foundation (under Grant CCF-0939370, Grant CNS-1836802, Grant CNS-1814477, and Grant CCF-1908308) | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Published Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Noor-A-Rahim, Md., Liu, Z., Lee, H., Khyam, M.O., He, J., Pesch, D., Moessner, K., Saad, W. and Poor, H.V. (2022) ‘6g for vehicle-to-everything (V2x) communications: enabling technologies, challenges, and opportunities’, Proceedings of the IEEE, 110(6), pp. 712–734. doi: 10.1109/JPROC.2022.3173031 | en |
dc.identifier.doi | 10.1109/JPROC.2022.3173031 | en |
dc.identifier.endpage | 734 | en |
dc.identifier.issn | 0018-9219 | |
dc.identifier.issued | 6 | en |
dc.identifier.journaltitle | Proceedings of The IEEE | en |
dc.identifier.startpage | 712 | en |
dc.identifier.uri | https://hdl.handle.net/10468/13690 | |
dc.identifier.volume | 110 | en |
dc.language.iso | en | en |
dc.publisher | IEEE | en |
dc.relation.project | info:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2077/IE/CONNECT: The Centre for Future Networks & Communications/ | en |
dc.relation.project | info:eu-repo/grantAgreement/EC/H2020::MSCA-COFUND-FP/713567/EU/Cutting Edge Training - Cutting Edge Technology/EDGE | en |
dc.relation.project | info:eu-repo/grantAgreement/EC/H2020::RIA/857034/EU/5G HEalth AquacultuRe and Transport validation trials/5G-HEART | en |
dc.relation.project | info:eu-repo/grantAgreement/EC/H2020::RIA/101016499/EU/Dynamic coverage Extension and Distributed Intelligence for human Centric applications with assured security, privacy and trust: from 5G to 6G/DEDICAT 6G | en |
dc.relation.project | info:eu-repo/grantAgreement/EC/H2020::MSCA-RISE/824019/EU/Cooperative Connected Intelligent Vehicles for Safe and Efficient Road Transport/COSAFE | en |
dc.relation.project | info:eu-repo/grantAgreement/EC/H2020::MSCA-IF-EF-ST/101022280/EU/Enhanced 5G Vehicle to Vehicle Technologies for Safe and Reliable Connected Autonomous Vehicles Applications/VESAFE | en |
dc.relation.project | info:eu-repo/grantAgreement/NSF/Directorate for Computer & Information Science & Engineering::Division of Computing and Communication Foundations/0939370/US/Emerging Frontiers of Science of Information/ | en |
dc.relation.project | info:eu-repo/grantAgreement/NSF/Directorate for Computer & Information Science & Engineering::Division of Computer and Network Systems/1836802/US/ICE-T: RC: Towards Highly Reliable Low Latency Broadband (HRLLBB) Communications over Wireless Heterogeneous Networks/ | en |
dc.relation.project | info:eu-repo/grantAgreement/NSF/Directorate for Computer & Information Science & Engineering::Division of Computer and Network Systems/1814477/US/NeTS: Small: Fundamentals of Internet-of-Things with Energy Harvesting and Edge Intelligence/ | en |
dc.relation.uri | https://doi.org/10.1109/JPROC.2022.3173031 | |
dc.rights | © 2022 the authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | Federated learning | en |
dc.subject | Intelligent reflective surfaces (IRSs) | en |
dc.subject | Machine learning (ML) | en |
dc.subject | Nonorthogonal multiple access (NOMA) | en |
dc.subject | Quantum | en |
dc.subject | Radio frequency (RF)-visible light communication (VLC) vehicle-to-everything (V2X) | en |
dc.subject | Sixth-generation (6G)-V2X | en |
dc.subject | Tactile-V2X | en |
dc.subject | Terahertz (THz) communications | en |
dc.subject | Unmanned-aerial-vehicle (UAV)/satelliteassisted V2X | en |
dc.subject | Vehicle-to-everything | en |
dc.subject | 6G mobile communication | en |
dc.subject | NOMA | en |
dc.subject | Wireless communication | en |
dc.subject | Security | en |
dc.subject | Vehicle-to-infrastructure | en |
dc.subject | Vehicle safety | en |
dc.title | 6G for vehicle-to-everything (V2X) communications: Enabling technologies, challenges, and opportunities | en |
dc.type | Article (peer-reviewed) | en |
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