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The Role of Machine Learning in the Advancement of 6G Technology: Opportunities and Challenges

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6G Enabled Fog Computing in IoT

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Abstract

While the world is heading towards the 5G network-oriented revolution, the implicit limitations of 5G have garnered researchers’ attention. Smart IoE (Internet of Everything) services are expected to grow. 6G, with its ultra-broadband, low latency, the decentralized and intelligent network is envisioned as a possible solution even at its infancy stage. Mobile Edge computing integrated with the Internet of Things (IoT) has eased information flow but has also complicated it. AI modeling is imperative for a 6G wireless decentralized network to move to ‘connected intelligence’ rather than ‘connected things.’ Modeling, training, and decision-making on local devices would aid in the integration of network nodes. This paper presents the recent advancements in the 6G network along with the plausible limitations and challenges in massive data procurement from IoT devices over 6G. The present use cases of IoT, Artificial intelligence, and the prospective application areas of 6G are discussed and analyzed. Further, we also posit how Artificial intelligence can maneuver the processing overheads of data processing. This paper also presents the architectural nuances of 6G that would pave the path for a fast and robust network.

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Authors and Affiliations

  1. Department of Computer Science, Central University of Rajasthan, Ajmer, India

    Krishna Kumar Mohbey & Malika Acharya

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  1. Krishna Kumar Mohbey
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  2. Malika Acharya
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Editors and Affiliations

  1. Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Mohit Kumar

  2. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK

    Sukhpal Singh Gill

  3. Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Jitendra Kumar Samriya

  4. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK

    Steve Uhlig

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Mohbey, K.K., Acharya, M. (2023). The Role of Machine Learning in the Advancement of 6G Technology: Opportunities and Challenges. In: Kumar, M., Gill, S.S., Samriya, J.K., Uhlig, S. (eds) 6G Enabled Fog Computing in IoT. Springer, Cham. https://doi.org/10.1007/978-3-031-30101-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-30101-8_13

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