Research on trust mechanism of C-V2X
C-V2X (Cellular Vehicle-to-Everything) has become a profound reform and innovative technology in automotive and communication industries. Through C-V2X communication, the nearby traffic participants can exchange real-time information, such as status ...
Xi Yifan +6 more
doaj +1 more source
Sidelink communication technology enhancement and standardization evolution for C-V2X
With the rapid development of intelligent transportation systems, sidelink communication technology for cellular vehicle-to-everything (C-V2X) has become the key technology to enable vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to ...
ZHAO Rui +6 more
doaj
Target Positioning Accuracy of V2X Sidelink Joint Communication and Sensing [PDF]
Joint communication and sensing (JCS) is gaining popularity in vehicular scenarios for detecting and localizing nearby objects or other vehicles using vehicle-to-everything (V2X) communications, thus complementing or improving on-board sensors.
Caterina Giovannetti +4 more
core +1 more source
Design & Development of FR1 Band Antenna for V2X Communication [PDF]
The developing trends in the automotive industry are evolving towards connected and autonomous vehicles that provide various advantages namely enhanced safety & security, congestion less traffic, smart mobility, and environmental sustainability at a ...
KG, Sujanth Narayan, Mr
core +1 more source
Auditable De-anonymization in V2X Communication [PDF]
Masoud Naderpour +3 more
openaire +1 more source
A Compact Multiband Shark-Fin Antenna for Integrated V2X Communication Systems. [PDF]
Ding X, Zha W, Feng B, Ou Y, Sim CY.
europepmc +1 more source
VANET supporting V2X communication by taking advantage of clustering.
VANET supporting V2X communication by taking advantage of clustering.
Venugopal Pakala (17775764) +1 more
core +1 more source
Extremely Large-Aperture Arrays for V2X Communication, Localization and Sensing. [PDF]
Decarli N +5 more
europepmc +1 more source
A V2X communication resource allocation method based on graph neural networks and deep reinforcement learning. [PDF]
Yu W, Yang X, Yu S.
europepmc +1 more source
Correction: Deep learning neural networks-based traffic predictors for V2X communication networks. [PDF]
Saady MM +6 more
europepmc +1 more source

