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Communication and Computation O-RAN Resource Slicing for URLLC Services Using Deep Reinforcement Learning

  • Published:2023-03 Issue:1 Volume:7 Page:66-73
  • ISSN:2471-2825
  • Container-title:IEEE Communications Standards Magazine
  • language:
  • Short-container-title:IEEE Comm. Stand. Mag.

Author:

Filali Abderrahime1,Nour Boubakr2,Cherkaoui Soumaya1,Kobbane Abdellatif3

Affiliation:

1. Polytechnique Montreal,Canada

2. Univeriste de Sherbrooke,Canada

3. UM5R ENSIAS,Morocco

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Management of Technology and Innovation,Law,Computer Networks and Communications,Safety, Risk, Reliability and Quality

Reference15 articles.

1. EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning

2. Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning;wu;IEEE JSAC,2020

3. Human-level control through deep reinforcement learning

4. Intelligent O-RAN for Beyond 5G and 6G Wireless Networks;niknam;ArXiv Preprint,2020

5. Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems

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1. Transfer learning-accelerated network slice management for next generation services;Computer Communications;2024-12

2. Enhancing Vehicular Networks With Hierarchical O-RAN Slicing and Federated DRL;IEEE Transactions on Green Communications and Networking;2024-09

3. Efficient Resource Allocation Framework for Network Slicing-enabled Open RAN;2024 Tenth International Conference on Communications and Electronics (ICCE);2024-07-31

4. Deep Learning Traffic Prediction and Resource Management for 5G RAN Slicing;Journal of The Institution of Engineers (India): Series B;2024-07-15

5. Delay-sensitive resource allocation for IoT systems in 5G O-RAN networks;Internet of Things;2024-07
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