The Roadmap to 6G: AI Empowered Wireless Networks
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The recent upsurge of diversified mobile applications, especially those supported by AI, is spurring heated discussions on the future evolution of wireless communications. While 5G is being deployed around the world, efforts from industry and academia have started to look beyond 5G and conceptualize 6G. We envision 6G to undergo an unprecedented transformation that will make it substantially different from the previous generations of wireless cellular systems. In particular, 6G will go beyond mobile Internet and will be required to support ubiquitous AI services from the core to the end devices of the network. Meanwhile, AI will play a critical role in designing and optimizing 6G architectures, protocols, and operations. In this article, we discuss potential technologies for 6G to enable mobile AI applications, as well as AI-enabled methodologies for 6G network design and optimization. Key trends in the evolution to 6G will also be discussed.
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Edge device distributed inference based on wireless MapReduce enjoys the advantages of providing low-latency, high-accurate, scalable, and resilient services for edge devices without accessing the cloud data center.
“Edge device distributed inference based on wireless MapReduce enjoys the advantages of providing low-latency, high-accurate, scalable, and resilient services for edge devices without accessing the cloud data center [12], [29].”
From Edge artificial intelligence for 6g: vision, enabling technologies, and applications (2022) · cites this paper as [12]
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- Authors
- Letaief, K. B., Chen, W., Shi, Y., Zhang, J., & Zhang, Y.-J. A.
- Affiliations
- Hong Kong University of Science and Technology (HK)
- Tsinghua University (CN)
- ShanghaiTech University (CN)
- Hong Kong Polytechnic University (HK)
- Chinese University of Hong Kong (HK)
- Venue
- IEEE Communications Magazine
- Published
- 2019-08
- Volume
- 57
- Issue
- 8
- Pages
- 84-90
- ISSN
- 0163-6804 (ISSN-L)
- 1558-1896
- OpenAlex
- W2941088479
- Cited by
- 2,207
- References
- 2
- Citations by year
- 2026: 233 · 2025: 289 · 2024: 325 · 2023: 344 · 2022: 384 · 2021: 394 · 2020: 223 · 2019: 15
- FWCI
- 91.31
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Communications Magazine (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
- Keywords
- 6G, artificial intelligence, wireless networks, network optimization, 5G
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