N. H. Mahmood, H. Alves, O. A. López, M. Shehab, D. P. M. Osorio and M. Latva-Aho, "Six Key Features of Machine Type Communication in 6G," 2020 2nd 6G Wireless Summit (6G SUMMIT), Levi, Finland, 2020, pp. 1-5, doi: 10.1109/6GSUMMIT49458.2020.9083794
Six key features of machine type communication in 6G
|Author:||Mahmood, Nurul Huda1; Alves, Hirley1; López, Onel Alcaraz1;|
16Gflagship.com, University of Oulu, Finland
2Department of Electrical Engineering, Federal University of São Carlos, São Carlos, SP, Brazil
|Online Access:||PDF Full Text (PDF, 0.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020071347264
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-07-13
While 5G is being rolled out in different parts of the globe, several research groups around the world have already started posing the question: What will the sixth generation (6G) be? The 6G vision is a data-driven society, enabled by near instant unlimited wireless connectivity. Driven by the impetus to provide vertical-specific wireless network solutions, machine type communication encompassing both its mission critical and massive connectivity aspects is foreseen to be an important cornerstone of 6G development. An over-arching vision for machine type communication in 6G networks is presented in paper. In this regard, some relevant performance indicators are first discussed, followed by a presentation of key enablers.
|Pages:||1 - 5|
Proceedings of the 2nd 6G Wireless Summit (6G SUMMIT), 17-20 March 2020 Levi, Finland
6G Wireless Summit
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work has been performed under the Academy of Finland 6Genesis Flagship program (grant no. 318927). The authors would like to acknowledge the contributions of their colleagues in the project, although the views
expressed in this work are those of the authors and do not necessarily represent the project. The work of Diana
P. Moya Osorio is partially supported by S˜ao Paulo Research Foundation (grant no. FAPESP 2017/20990-6).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
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