Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches
Tohoku University · Northwestern Polytechnical University
Abstract
As a powerful tool, the vehicular network has been built to connect human communication and transportation around the world for many years to come. However, with the rapid growth of vehicles, the vehicular network becomes heterogeneous, dynamic, and large scaled, which makes it difficult to meet the strict requirements, such as ultralow latency, high reliability, high security, and massive connections of the next-generation (6G) network. Recently, machine learning (ML) has emerged as a powerful artificial intelligence (AI) technique to make both the vehicle and wireless communication highly efficient and adaptable. Naturally, employing ML into vehicular communication and network becomes a hot topic and is…
Citation impact
- FWCI
- 43.71
- Percentile
- 100%
- References
- 144
Authors
4- FTFengxiao TangCorresponding
Tohoku University
- YKYuichi Kawamoto
Tohoku University
- NKNei Kato
Tohoku University
- JLJiajia Liu
Northwestern Polytechnical University
Topics & keywords
- Computer science
- Reliability (semiconductor)
- Latency (audio)
- Wireless
- Vehicular communication systems
- Wireless network
- Low latency (capital markets)
- Intelligent transportation system
- Industry, innovation and infrastructure