The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
A Survey on Green 6G Network: Architecture and Technologies
Open accessAbstract
While 5G is being commercialized worldwide, research institutions around the world have started to look beyond 5G and 6G is expected to evolve into green networks, which deliver high Quality of Service and energy efficiency. To meet the demands of future applications, significant improvements need to be made in mobile network architecture. We envision 6G undergoing unprecedented breakthrough and integrating traditional terrestrial mobile networks with emerging space, aerial and underwater networks to provide anytime anywhere network access. This paper presents a detailed survey on wireless evolution towards 6G networks. In this survey, the prime focus is on the new architectural changes associated with 6G networks, characterized by ubiquitous 3D coverage, introduction of pervasive AI and enhanced network protocol stack. Along with this, we discuss related potential technologies that are helpful in forming sustainable and socially seamless networks, encompassing terahertz and visible light communication, new communication paradigm, blockchain and symbiotic radio. Our work aims to provide enlightening guidance for subsequent research of green 6G.
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Cites
Wireless communications with unmanned aerial vehicles: opportunities and challenges
Zeng, Y., Zhang, R., & Lim, T. J. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7470933 · Cited by 4,048
A Survey of 5G Network: Architecture and Emerging Technologies
Gupta, A., & Jha, R. K. (2015) · IEEE Access · doi:10.1109/access.2015.2461602 · Cited by 2,420
A Comprehensive Survey of Recent Advancements in Molecular Communication
Farsad, N., Yilmaz, H. B., Eckford, A., Chae, C.-B., & Guo, W. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2527741 · Cited by 968
Intelligent 5G: When Cellular Networks Meet Artificial Intelligence
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Ahmad, I., Shahabuddin, S., Kumar, T., Okwuibe, J., Gurtov, A., & Ylianttila, M. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2916180 · Cited by 366
Robust Mobile Crowd Sensing: When Deep Learning Meets Edge Computing
Zhou, Z., Liao, H., Gu, B., Huq, K. M. S., Mumtaz, S., & Rodriguez, J. (2018) · IEEE Network · doi:10.1109/mnet.2018.1700442 · Cited by 260
FSO-Based Vertical Backhaul/Fronthaul Framework for 5G+ Wireless Networks
Alzenad, M., Shakir, M. Z., Yanikomeroglu, H., & Alouini, M.-S. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600735 · Cited by 49
Cited by
On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds
Wang, C.-X., You, X., Gao, X., Zhu, X., Li, Z., Zhang, C., Wang, H., Huang, Y., Chen, Y., Haas, H., et al. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3249835 · Cited by 2,336
Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research
Alwis, C. D., Kalla, A., Pham, Q.-V., Kumar, P., Dev, K., Hwang, W.-J., & Liyanage, M. (2021) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2021.3071496 · Cited by 788
Federated learning for 6G communications: Challenges, methods, and future directions
Liu, Y., Yuan, X., Xiong, Z., Kang, J., Wang, X., & Niyato, D. (2020) · China Communications · doi:10.23919/jcc.2020.09.009 · Cited by 464
“optimizing the balance between energy demand and supply [11].”
BackgroundInfluentialSecurity and privacy in 6G networks: New areas and new challenges
Wang, M., Zhu, T., Zhang, T., Zhang, J., Yu, S., & Zhou, W. (2020) · Digital Communications and Networks · doi:10.1016/j.dcan.2020.07.003 · Cited by 363
Imoize, A. L., Adedeji, O., Tandiya, N., & Shetty, S. (2021) · Sensors · doi:10.3390/s21051709 · Cited by 281
Metadata
- Authors
- Huang, T., Yang, W., Wu, J., Ma, J., Zhang, X., & Zhang, D.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 175758-175768
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2993508366
- Cited by
- 562
- References
- 7
- FWCI
- 23.62
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
