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Wave: A tutorial
Abstract
Intelligent transportation systems have been under development since at least the early 1990s. The rationale behind the concept is to automate the interactions among vehicles and infrastructure to achieve high levels of security, comfort, and efficiency. Communications, in general, and networking, in particular, have been essential elements in the evolution of these systems. The IEEE has developed a system architecture known as WAVE to provide wireless access in vehicular environments. This article gives an overview of the associated standards. The presentation loosely follows the order of the layers of the open systems interconnection model.
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Citations
Cited by
5G for Vehicular Communications
Shah, S. A. A., Ahmed, E., Imran, M., & Zeadally, S. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700467 · Cited by 363
Connected Car: Technologies, Issues, Future Trends
Coppola, R., & Morisio, M. (2017) · ACM Computing Surveys · doi:10.1145/2971482 · Cited by 283
Djahel, S., Jabeur, N., Barrett, R., & Murphy, J. (2015) · 2015 International Symposium on Networks, Computers and Communications (ISNCC) · doi:10.1109/isncc.2015.7238584 · Cited by 79
Metadata
- Authors
- Uzcategui, R. A., De Sucre, A. J., & Acosta-Marum, G.
- Venue
- IEEE Communications Magazine
- Published
- 2009-05
- Volume
- 47
- Issue
- 5
- Pages
- 126-133
- ISSN
- 0163-6804 (ISSN-L)
- 1558-1896
- OpenAlex
- W2162455895
- Cited by
- 466
- References
- 0
- FWCI
- 27.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Wave: A tutorial. https://app.cochat.ai/papers/10.1109/mcom.2009.4939288
- The paper
- Uzcategui, R. A., De Sucre, A. J., & Acosta-Marum, G. (2009). Wave: A tutorial. IEEE Communications Magazine. https://doi.org/10.1109/mcom.2009.4939288
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
