articleProceedings of the IEEEDec 6, 2019Closed access

Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches

Tohoku University · Northwestern Polytechnical University

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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

624
total citations
FWCI
43.71
Percentile
100%
References
144
Citations per year

Authors

4

Topics & keywords

Keywords
  • Computer science
  • Reliability (semiconductor)
  • Latency (audio)
  • Wireless
  • Vehicular communication systems
  • Wireless network
  • Low latency (capital markets)
  • Intelligent transportation system
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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