TY - JOUR
T1 - 6G for Vehicle-to-Everything (V2X) Communications
T2 - Enabling Technologies, Challenges, and Opportunities
AU - Noor-A-Rahim, Md
AU - Liu, Zilong
AU - Lee, Haeyoung
AU - Khyam, Mohammad Omar
AU - He, Jianhua
AU - Pesch, Dirk
AU - Moessner, Klaus
AU - Saad, Walid
AU - Poor, H. Vincent
N1 - Funding Information:
This work was supported in part by 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); in part by the 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; and in part by the U.S. National Science Foundation under Grant CCF-0939370, Grant CNS-1836802, Grant CNS-1814477, and Grant CCF-1908308.
Publisher Copyright:
© 1963-2012 IEEE.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - 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.
AB - 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.
KW - Blockchain
KW - brain-controlled vehicle (BCV)
KW - federated learning
KW - intelligent reflective surfaces (IRSs)
KW - machine learning (ML)
KW - nonorthogonal multiple access (NOMA)
KW - quantum
KW - radio frequency (RF)-visible light communication (VLC) vehicle-to-everything (V2X)
KW - sixth-generation (6G)-V2X
KW - tactile-V2X
KW - terahertz (THz) communications; unmanned-aerial-vehicle (UAV)/satelliteassisted V2X
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U2 - 10.1109/JPROC.2022.3173031
DO - 10.1109/JPROC.2022.3173031
M3 - Article
AN - SCOPUS:85130498686
SN - 0018-9219
VL - 110
SP - 712
EP - 734
JO - Proceedings of the Institute of Radio Engineers
JF - Proceedings of the Institute of Radio Engineers
IS - 6
ER -