6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies
Abstract
A key enabler for the intelligent information society of 2030, 6G networks are expected to provide performance superior to 5G and satisfy emerging services and applications. In this article, we present our vision of what 6G will be and describe usage scenarios and requirements for multi-terabyte per second (Tb/s) and intelligent 6G networks. We present a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks to provide ubiquitous and unlimited wireless connectivity. We also discuss artificial intelligence (AI) and machine learning [1], [2] for autonomous networks and innovative air-interface design. Finally, we identify several promising technologies for the 6G ecosystem, including terahertz (THz) communications, very-large-scale antenna arrays [i.e., supermassive (SM) multiple-input, multiple-output (MIMO)], large intelligent surfaces (LISs) and holographic beamforming (HBF), orbital angular momentum (OAM) multiplexing, laser and visible-light communications (VLC), blockchain-based spectrum sharing, quantum communications and computing, molecular communications, and the Internet of Nano-Things.
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Cell therapy research is carried out for critical disease treatment.
“For instance, cell therapy research is carried out for critical disease treatment [47], [48].”
From 6G Communication Technology: A Vision on Intelligent Healthcare (2021) · cites this paper as [48]
Cites
Visible Light Communication, Networking, and Sensing: A Survey, Potential and Challenges
Pathak, P. H., Feng, X., Hu, P., & Mohapatra, P. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2476474 · Cited by 1,553 · see citing works
Space-Air-Ground Integrated Network: A Survey
Liu, J., Shi, Y., Fadlullah, Z. M., & Kato, N. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2841996 · Cited by 1,281 · see citing works
Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions
Afolabi, I., Taleb, T., Samdanis, K., Ksentini, A., & Flinck, H. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2815638 · Cited by 1,078 · see citing works
Massive MIMO is a reality—What is next?
Björnson, E., Sanguinetti, L., Wymeersch, H., Hoydis, J., & Marzetta, T. L. (2019) · Digital Signal Processing · doi:10.1016/j.dsp.2019.06.007 · Cited by 839 · see citing works
Deep Learning for Intelligent Wireless Networks: A Comprehensive Survey
Mao, Q., Hu, F., & Hao, Q. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2846401 · Cited by 789 · see citing works
6G Vision and Requirements: Is There Any Need for Beyond 5G?
David, K., & Berndt, H. (2018) · IEEE Vehicular Technology Magazine · doi:10.1109/mvt.2018.2848498 · Cited by 729 · see citing works
A Tutorial on IEEE 802.11ax High Efficiency WLANs
Khorov, E., Kiryanov, A., Lyakhov, A. I., & Bianchi, G. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2871099 · Cited by 597 · see citing works
Kotobi, K., & Bilén, S. G. (2018) · IEEE Vehicular Technology Magazine · doi:10.1109/mvt.2017.2740458 · Cited by 203 · see citing works
Ren, Y., Li, L., Xie, G., Yan, Y., Cao, Y., Huang, H., Ahmed, N., Zhao, Z., Liao, P., Zhang, C., et al. (2017) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2017.2675885 · Cited by 187 · see citing works
Fundamentals of Molecular Information and Communication Science
Akan, Ö. B., Ramezani, H., Khan, T., Abbasi, N. A., & Kuşcu, M. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2537306 · Cited by 178 · see citing works
Quantum Search Algorithms for Wireless Communications
Botsinis, P., Alanis, D., Babar, Z., Nguyen, H. V., Chandra, D., Ng, S. X., & Hanzo, L. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2882385 · Cited by 149 · see citing works
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Giordani, M., Polese, M., Mezzavilla, M., Rangan, S., & Zorzi, M. (2020) · IEEE Communications Magazine · doi:10.1109/mcom.001.1900411 · Cited by 2,241 · see citing works
Dang, S., Amin, O., Shihada, B., & Alouini, M.-S. (2020) · Nature Electronics · doi:10.1038/s41928-019-0355-6 · Cited by 1,790 · see citing works
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Gui, G., Liu, M., Tang, F., Kato, N., & Adachi, F. (2020) · IEEE Wireless Communications · doi:10.1109/mwc.001.1900516 · Cited by 733 · see citing works
Security and Privacy for 6G: A Survey on Prospective Technologies and Challenges
Nguyen, V.-L., Lin, P.-C., Cheng, B.-C., Hwang, R.-H., & Lin, Y.-D. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3108618 · Cited by 515 · see citing works
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 · see citing works
“According to ITU-T’s 6G communication technology white paper, beyond and high-precision teleport technology will provide users with a variety of new services [1]–[4], [13].”
BackgroundBlockchain for 5G and beyond networks: A state of the art survey
Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102693 · Cited by 412 · see citing works
Yigitcanlar, T., Mehmood, R., & Corchado, J. M. (2021) · Sustainability · doi:10.3390/su13168952 · Cited by 319 · see citing works
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Sun, Y., Liu, J., Wang, J., Cao, Y., & Kato, N. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3011561 · Cited by 211 · see citing works
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Wang, S., Qureshi, M. A., Miralles-Pechuán, L., Huynh-The, T., Gadekallu, T. R., & Liyanage, M. (2024) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2024.3386872 · Cited by 170 · see citing works
Quy, V. K., Chehri, A., Quy, N. M., Han, N. D., & Ban, N. T. (2023) · IEEE Access · doi:10.1109/access.2023.3269297 · Cited by 164 · see citing works
Toward immersive communications in 6G
Shen, X. (., Gao, J., Li, M., Zhou, C., Hu, S., He, M., & Zhuang, W. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.1068478 · Cited by 124 · see citing works
The impact of 6G-IoT technologies on the development of agriculture 5.0: a review
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Getu, T. M., Kaddoum, G., & Bennis, M. (2024) · Proceedings of the IEEE · doi:10.1109/jproc.2024.3520707 · Cited by 110 · see citing works
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Nayak, S., & Patgiri, R. (2021) · Studies in Computational Intelligence · doi:10.1007/978-981-15-9735-0_1 · Cited by 143 · see citing works
6G: Connecting Everything by 1000 Times Price Reduction
Zhang, S., Xiang, C., & Xu, S. (2020) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2020.2980003 · Cited by 105 · see citing works
A roadmap of next-generation wireless technology for 6g-enabled vehicular networks
Adhikari, M., Hazra, A., Menon, V. G., Chaurasia, B. K., & Mumtaz, S. (2021) · IEEE Internet of Things Magazine · doi:10.1109/iotm.001.2100075 · Cited by 55 · see citing works
Hassan, S. S., Min Park, Y., Tun, Y. K., Saad, W., Han, Z., & Hong, C. S. (2022) · ICC 2022 - IEEE International Conference on Communications · doi:10.1109/icc45855.2022.9838676 · Cited by 34 · see citing works
Redefining 6G Network Slicing: AI-Driven Solutions for Future Use Cases
Botez, R., Zinca, D., & Dobrota, V. (2025) · Electronics · doi:10.3390/electronics14020368 · Cited by 29 · see citing works
- Authors
- Zhang, Z., Xiao, Y., Ma, Z., Xiao, M., Ding, Z., Lei, X., Karagiannidis, G. K., & Fan, P.
- Affiliations
- Southwest Jiaotong University (CN)
- KTH Royal Institute of Technology (SE)
- University of Manchester (GB)
- Aristotle University of Thessaloniki (GR)
- ORCID
- Venue
- IEEE Vehicular Technology Magazine
- Published
- 2019-09
- Volume
- 14
- Issue
- 3
- Pages
- 28-41
- ISSN
- 1556-6072 (ISSN-L)
- 1556-6080
- OpenAlex
- W2964005248
- Cited by
- 2,575
- References
- 12
- Citations by year
- 2026: 256 · 2025: 398 · 2024: 440 · 2023: 470 · 2022: 405 · 2021: 407 · 2020: 191 · 2019: 7 · 2018: 1
- FWCI
- 90.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Vehicular Technology Magazine (publishedVersion)
- Funders
- National Natural Science Foundation of China NSFC Key Project (61731017)
- NSFC Project (61871334)
- NSFC China-Swedish Project (6161101297)
- 111 Project (111-2-14)
- Sichuan Science and Techology Program (2017HH0035)
- Fundamental Research Funds for the Central Universities (61501382)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Physical Sciences › Engineering › Aerospace Engineering › Satellite Communication Systems
- Keywords
- 6G, 6G network architecture, autonomous networks, air interface design, terahertz communication, large intelligent surfaces, holographic beamforming, orbital angular momentum multiplexing, visible light communication, laser communication, quantum communication, molecular communication, Internet of Nano Things
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