4.7 Article

Artificial-Intelligence-Enabled Intelligent 6G Networks

Journal

IEEE NETWORK
Volume 34, Issue 6, Pages 272-280

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.011.2000195

Keywords

6G mobile communication; Sensors; Computer architecture; Data mining; Deep learning; Support vector machines

Funding

  1. National Research Foundation (NRF), Singapore, under Singapore Energy Market Authority (EMA), Energy Resilience [NRF2017EWT-EP003-041, NRF2015-NRF-ISF001-2277]
  2. Singapore NRF National Satellite of Excellence, Design Science and Technology for Secure Critical Infrastructure [NSoE DeST-SCI2019-0007, NSoE DeST-SCI2019-0012]
  3. A*STAR-NTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing [RGANS1906]
  4. Wallenberg AI, Autonomous Systems and Software Program and Nanyang Technological University (WASP/NTU) [M4082187 (4080)]
  5. Singapore Ministry of Education (MOE) [RG16/20]
  6. Alibaba Group through Alibaba Innovative Research (AIR) Program
  7. Singapore Ministry of Education Academic Research Fund [Tier 1 RG128/18, Tier 1 RG115/19, Tier 1 RT07/19, Tier 1 RT01/19, Tier 2 MOE2019-T2-1-176]
  8. Singapore National Research Foundation (NRF) under its Strategic Capability Research Centres Funding Initiative: Strategic Centre for Research in Privacy-Preserving Technologies & Systems (SCRIPTS)
  9. Energy Research Institute @ NTU (ERIAN)
  10. AI Singapore (AISG) 100 Experiments (100E) programme
  11. Nanyang Technological University (NTU)
  12. NTU-WeBank JRI [NWJ-2020-004]
  13. NUJ Project for Large Vertical Take-Off & Landing (VTOL) Research Platform
  14. NTU-WASP Joint Project
  15. Alibaba-NTU Singapore Joint Research Institute (JRI)

Ask authors/readers for more resources

With the rapid development of smart terminals and infrastructures, as well as diversified applications (e.g., virtual and augmented reality, remote surgery and holographic projection) with colorful requirements, current networks (e.g., 4G and upcoming 5G networks) may not be able to completely meet quickly rising traffic demands. Accordingly, efforts from both industry and academia have already been put to the research on 6G networks. Recently, artificial intelligence (Ai) has been utilized as a new paradigm for the design and optimization of 6G networks with a high level of intelligence. Therefore, this article proposes an Ai-enabled intelligent architecture for 6G networks to realize knowledge discovery, smart resource management, automatic network adjustment and intelligent service provisioning, where the architecture is divided into four layers: intelligent sensing layer, data mining and analytics layer, intelligent control layer and smart application layer. We then review and discuss the applications of Ai techniques for 6G networks and elaborate how to employ the Ai techniques to efficiently and effectively optimize the network performance, including Ai-empowered mobile edge computing, intelligent mobility and handover management, and smart spectrum management. We highlight important future research directions and potential solutions for Ai-enabled intelligent 6G networks, including computation efficiency, algorithms robustness, hardware development and energy management.

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