mlsanityData to 7 Oct 2026

Deep Reinforcement Learning for Resource Management in Network Slicing

arXiv 1805.06591 ↗First posted 17 May 2018cs.NI cs.LGcited by 27

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Abstract (arXiv)

Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices. In order to provide better-performing and cost-efficient services, network slicing involves challenging technical issues and urgently looks forward to intelligent innovations to make the resource management consistent with users' activities per slice. In that regard, deep reinforcement learning (DRL), which focuses on how to interact with the environment by trying alternative actions and reinforcing the tendency actions producing more rewarding consequences, is assumed to be a promising solution. In this paper, after briefly reviewing the fundamental concepts of DRL, we investigate the application of DRL in solving some typical resource management for network slicing scenarios, which include radio resource slicing and priority-based core network slicing, and demonstrate the advantage of DRL over several competing schemes through extensive simulations. Finally, we also discuss the possible challenges to apply DRL in network slicing from a general perspective.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 May 2018.

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Citing papers per year: 2021: 6; 2022: 4; 2023: 7; 2024: 4; 2025: 3; 2026: 3.

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  1. 2021Reinforcement Learning-powered Semantic Communication via Semantic Similaritycited by 15
  2. 2021Age of Information Aware VNF Scheduling in Industrial IoT Using Deep Reinforcement Learningcited by 8
  3. 2021CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicingcited by 7
  4. 2023Digital Twin-Enhanced Deep Reinforcement Learning for Resource Management in Networks Slicingcited by 7
  5. 2021Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicingcited by 6
  6. 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examplescited by 5
  7. 2023Safe and Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning Approachcited by 5
  8. 2023Anytime-Constrained Reinforcement Learningcited by 5
  9. 2024Deterministic Policies for Constrained Reinforcement Learning in Polynomial Timecited by 5
  10. 2023Generalizable Resource Scaling of 5G Slices using Constrained Reinforcement Learningcited by 4
  11. 2026ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunitiescited by 4
  12. 2021Can You Fix My Neural Network? Real-Time Adaptive Waveform Synthesis for Resilient Wireless Signal Classificationcited by 3
15 more
  1. 20266GAgentGym: Tool Use, Data Synthesis, and Agentic Learning for Network Managementcited by 3
  2. 2021Federated learning and next generation wireless communications: A survey on bidirectional relationshipcited by 2
  3. 2022On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RANcited by 1
  4. 2022Deep Reinforcement Learning for Combined Coverage and Resource Allocation in UAV-aided RAN-slicingcited by 1
  5. 2024Anytime-Constrained Equilibria in Polynomial Timecited by 1
  6. 2025Polynomial-Time Approximability of Constrained Reinforcement Learningcited by 1
  7. 2025To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networkscited by 1
  8. 2022A Review of the Convergence of 5G/6G Architecture and Deep Learningcited by 0
  9. 2023A Deep RL Approach on Task Placement and Scaling of Edge Resources for Cellular Vehicle-to-Network Service Provisioningcited by 0
  10. 2023Inter-Cell Network Slicing With Transfer Learning Empowered Multi-Agent Deep Reinforcement Learningcited by 0
  11. 2023Robust Network Slicing: Multi-Agent Policies, Adversarial Attacks, and Defensive Strategiescited by 0
  12. 2024WirelessAgent: Large Language Model Agents for Intelligent Wireless Networkscited by 0
  13. 2024A hybrid solution for 2-UAV RAN slicingcited by 0
  14. 2025Meta Hierarchical Reinforcement Learning for Scalable Resource Management in O-RANcited by 0
  15. 2026When Adaptive Rewards Hurt: Causal Probing and the Switching-Stability Dilemma in LLM-Guided LEO Satellite Schedulingcited by 0