Vehicle-to-Everything Projects for ME, MTech, Masters, MS abroad, and PhD students. These Vehicle-to-Everything ieee projects are implemented with future work and extension for final year students with research paper writing and publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Vehicle-to-Everything Projects
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Cloud-native orchestration framework for network slice federation across administrative domains in 5G/6G mobile networks
This project focuses on improving mobile networks for connected and automated vehicles. It ensures that users keep a smooth connection even when moving between different network operators. The researchers designed a system that allows mobile operators to share network resources efficiently. They tested it on a 5G platform and studied how different strategies affect performance. -
On the Impact of Re-Evaluation in 5G NR V2X Mode 2
This project studies how 5G technology helps cars communicate safely on the road. It looks at a feature called re-evaluation that checks for possible message collisions before sending data. The research finds that this feature works well for regular traffic but is less effective for irregular traffic. It also shows that while it can prevent some collisions, it adds extra work and may not greatly improve overall performance. -
Performance Characterization of Joint Communication and Sensing With Beyond 5G NR-V2X Sidelink
This project studies how future 5G vehicle networks can detect nearby objects using the same signals that cars use to communicate. It looks at how well vehicles can sense their surroundings when many cars share the network. The research also examines how network settings like bandwidth, signal type, and message size affect detection accuracy. The goal is to improve sensing without needing extra radar signals. -
Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed Solutions
This project studies how future 6G networks can improve communication between vehicles and other devices on the road. It looks at ways to share network resources fairly and efficiently while avoiding interference and collisions. The study also explores new techniques like machine learning and edge computing to make vehicle communication faster and more reliable. Overall, it aims to make connected vehicles safer and more efficient in a hyperconnected 6G environment.
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