The Roadmap to 6G - AI Empowered Wireless Networks

By Khaled Ben Letaief, Yuanming Shi, Jun Zhang, Ying-Jun Angela Zhang. 2019

1,666 citations recorded by the source corpus.

The recent upsurge of diversified mobile applications, especially those supported by Artificial Intelligence (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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Citations in the corpus

Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks (2019, background): “Due to the sheer volume of data generated by the end-user devices, as well as the increasing concerns about sharing private information, a new machine learning model, namely the federated learning (FL) [1–4], has emerged from the intersection of artiﬁcial intelligence and edge computing [5–7].”
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Communication-Efficient Edge AI: Algorithms and Systems (2020, background): “Futuristic wireless systems [11] mainly consist of ultra-dense edge nodes, including edge servers at the base stations and wireless access points, and edge devices such as smart phones, smart vehicles, and drones.”
A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications (2023, background): “The anticipated sixth generation (6G) of wireless networks, expected to serve communication needs beyond 2030, have sparked significant research interest due to the advent of novel requirements following the rapid evolution of wireless applications [6]–[12].”
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications (2021, background): “In particular, three new application services were envisioned for 6G, including computation oriented communications (COC), contextually agile eMBB communications (CAeC), and event deﬁned uRLLC (EDuRLLC) [12].”
A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges (2022, background): “, for users and sensor networks aiding in the physical-virtual world synchronization) [77], [78], [79].”
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6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions (2019, background): “[20] Possible technologies to enable mobile AI applications for 6G and AI-enabled approaches for 6G network design and optimization are discussed.”
A Tutorial on Fluid Antenna System for 6G Networks: Encompassing Communication Theory, Optimization Methods and Hardware Designs (2024, background): “…from around the world are constantly exploring different cutting-edge technologies, such as the integration of AI or machine learning (ML) [17], next-generation multiple access (NGMA) [18], [19], non-terrestrial networks (NTN) [20], reconfigurable intelligent surfaces (RIS) [21], [22],…”
Integrated Satellite-Terrestrial Networks Toward 6G: Architectures, Applications, and Challenges (2022, background): “Beyond the three main scenarios of eMBB, URLLC, and mMTC in the 5G network, new application scenarios are proposed for the 6G network [46], [47].”
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Reducing Offloading Latency for Digital Twin Edge Networks in 6G (2020, background): “…one of the key communication infrastructure components, mobile edge computing (MEC) promises to support the stringent performance requirements, new functions, and new intelligent services for all things big and small in future 6G networks, powered by artiﬁcial intelligence (AI) techniques [2], [3].”