mlsanityData to 14 Oct 2026

AI-Native Network Slicing for 6G Networks

arXiv 2105.08576 ↗First posted 18 May 2021cs.NI cs.LGcited by 31

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Abstract (arXiv)

With the global roll-out of the fifth generation (5G) networks, it is necessary to look beyond 5G and envision the 6G networks. The 6G networks are expected to have space-air-ground integrated networks, advanced network virtualization, and ubiquitous intelligence. This article presents an artificial intelligence (AI)-native network slicing architecture for 6G networks to enable the synergy of AI and network slicing, thereby facilitating intelligent network management and supporting emerging AI services. AI-based solutions are first discussed across network slicing lifecycle to intelligently manage network slices, i.e., AI for slicing. Then, network slicing solutions are studied to support emerging AI services by constructing AI instances and performing efficient resource management, i.e., slicing for AI. Finally, a case study is presented, followed by a discussion of open research issues that are essential for AI-native network slicing in 6G networks.

Key facts. Cited by 31 papers in the map (data through 14 Oct 2026). Builds on 7 of its 29 references that are in the map. First posted on arXiv 18 May 2021.

Builds on

7 of 29 references.

References · 7

  1. 2019The Roadmap to 6G -- AI Empowered Wireless Networkscited by 153
  2. 2019Towards 6G Networks: Use Cases and Technologiescited by 14
  3. 2020Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learningcited by 13
  4. 2020White Paper on Broadband Connectivity in 6Gcited by 10
  5. 2017Software Defined Space-Air-Ground Integrated Vehicular Networks: Challenges and Solutionscited by 8
  6. 2020Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in Space-Air-Ground Integrated Networkcited by 5
  7. 2021Slicing-Based AI Service Provisioning on Network Edgecited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 5; 2023: 9; 2024: 7; 2025: 4; 2026: 6.

31 papers.

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  1. 2022Less Data, More Knowledge: Building Next Generation Semantic Communication Networkscited by 62
  2. 2023Wireless Network Digital Twin for 6G: Generative AI as A Key Enablercited by 22
  3. 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6Gcited by 14
  4. 2023Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyondcited by 14
  5. 2023Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devicescited by 13
  6. 2024Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Thingscited by 6
  7. 2023Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integrationcited by 5
  8. 2023Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insightscited by 4
  9. 2024Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inferencecited by 4
  10. 2024The Energy Cost of Artificial Intelligence Lifecycle in Communication Networkscited by 4
  11. 2023Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communicationscited by 3
  12. 2024Learning to Slice Wi-Fi Networks: A State-Augmented Primal-Dual Approachcited by 2
19 more
  1. 2025Agoran: An Agentic Open Marketplace for 6G RAN Automationcited by 2
  2. 2023Domain Adaptation of Reinforcement Learning Agents based on Network Service Proximitycited by 1
  3. 2023Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicingcited by 1
  4. 2024Slicing for AI: An Online Learning Framework for Network Slicing Supporting AI Servicescited by 1
  5. 2026An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Tradingcited by 1
  6. 2026On Identifying Adversarial Intent Injection in AI-Native 6G Networkscited by 1
  7. 2022VHetNets for AI and AI for VHetNets: An Anomaly Detection Case Study for Ubiquitous IoTcited by 0
  8. 2022Deep Edge Intelligence: Architecture, Key Features, Enabling Technologies and Challengescited by 0
  9. 2022Reinforcement Learning Agent Design and Optimization with Bandwidth Allocation Modelcited by 0
  10. 2022Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networkscited by 0
  11. 2024Variational Source-Channel Coding for Semantic Communicationcited by 0
  12. 2024Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Networkcited by 0
  13. 2025A Representation Learning Approach to Feature Drift Detection in Wireless Networkscited by 0
  14. 2025Constellation as a Service: Tailored Connectivity Management in Direct-Satellite-to-Device Networkscited by 0
  15. 2025AI-driven Orchestration at Scale: Estimating Service Metrics on National-Wide Testbedscited by 0
  16. 2026Interpretable Attention-Based Multi-Agent PPO for Latency Spike Resolution in 6G RAN Slicingcited by 0
  17. 2026Adaptive RAN Slicing Control via Reward-Free Self-Finetuning Agentscited by 0
  18. 2026Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directionscited by 0
  19. 2026Privacy-Aware Agent Collaboration for Dynamic VR Slice Management in 6G SD-RANcited by 0