mlsanityData to 14 Oct 2026

Meta Reinforcement Learning Approach for Adaptive Resource Optimization in O-RAN

arXiv 2410.03737 ↗First posted 30 Sep 2024cs.NI cs.AI cs.LGcited by 8

On the map: Deep reinforcement learning methods → RL for energy, networks and operations

Abstract (arXiv)

As wireless networks grow to support more complex applications, the Open Radio Access Network (O-RAN) architecture, with its smart RAN Intelligent Controller (RIC) modules, becomes a crucial solution for real-time network data collection, analysis, and dynamic management of network resources including radio resource blocks and downlink power allocation. Utilizing artificial intelligence (AI) and machine learning (ML), O-RAN addresses the variable demands of modern networks with unprecedented efficiency and adaptability. Despite progress in using ML-based strategies for network optimization, challenges remain, particularly in the dynamic allocation of resources in unpredictable environments. This paper proposes a novel Meta Deep Reinforcement Learning (Meta-DRL) strategy, inspired by Model-Agnostic Meta-Learning (MAML), to advance resource block and downlink power allocation in O-RAN. Our approach leverages O-RAN's disaggregated architecture with virtual distributed units (DUs) and meta-DRL strategies, enabling adaptive and localized decision-making that significantly enhances network efficiency. By integrating meta-learning, our system quickly adapts to new network conditions, optimizing resource allocation in real-time. This results in a 19.8% improvement in network management performance over traditional methods, advancing the capabilities of next-generation wireless networks.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 13 of its 21 references that are in the map. First posted on arXiv 30 Sep 2024.

Builds on

13 of 21 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Open RAN LSTM Traffic Prediction and Slice Management using Deep Reinforcement Learning12 Jan

Other references · 12

  1. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,897
  2. 2023A Tutorial on Meta-Reinforcement Learningcited by 108
  3. 2022Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challengescited by 55
  4. 2022dApps: Distributed Applications for Real-time Inference and Control in O-RANcited by 17
  5. 2022Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RANcited by 11
  6. 2022Predictive Closed-Loop Service Automation in O-RAN based Network Slicingcited by 8
  7. 2022Intelligent Traffic Steering in Beyond 5G Open RAN based on LSTM Traffic Predictioncited by 7
  8. 2023Attention-based Open RAN Slice Management using Deep Reinforcement Learningcited by 7
  9. 2024DRL-based Latency-Aware Network Slicing in O-RAN with Time-Varying SLAscited by 5
  10. 2022Federated Meta-Learning for Traffic Steering in O-RANcited by 4
  11. 2023Meta Federated Reinforcement Learning for Distributed Resource Allocationcited by 4
  12. 2023Adaptive Resource Allocation for Virtualized Base Stations in O-RAN with Online Learningcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 3.

8 papers.

  1. 2025Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Surveycited by 14
  2. 2026ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunitiescited by 4
  3. 2025ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicingcited by 3
  4. 2025Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicingcited by 2
  5. 2025Task Specific Sharpness Aware O-RAN Resource Management using Multi Agent Reinforcement Learningcited by 1
  6. 2025Meta Hierarchical Reinforcement Learning for Scalable Resource Management in O-RANcited by 0
  7. 2026ORAN-DEFEND: Subspace Detection and Sanitization of Backdoor DRL xApps in Open RANcited by 0
  8. 2026Place, Slice and Schedule: Hierarchical O-RAN Control of a Tethered mmWave UAV-gNBcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Meta-Reinforcement Learning for Fast and Data-Efficient Spectrum Allocation in Dynamic Wireless Networks
  2. 2025Near-Real-Time Resource Slicing for QoS Optimization in 5G O-RAN using Deep Reinforcement Learning
  3. 2024Dynamics of Resource Allocation in O-RANs: An In-depth Exploration of On-Policy and Off-Policy Deep Reinforcement Learning for Real-Time Applications
  4. 2025Optimisation of Resource Allocation in Heterogeneous Wireless Networks Using Deep Reinforcement Learning
  5. 2025QoS-Aware Dynamic CU Selection in O-RAN with Graph-Based Reinforcement Learning
  6. 2026Scalable machine learning-based approaches for energy saving in densely deployed Open RAN ↗
  7. 2025Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless Networks
  8. 2025Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization