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Deep reinforcement learning based flexible preamble allocation for RAN slicing in 5G networks

  • Published:2022-10 Issue: Volume:215 Page:109202
  • ISSN:1389-1286
  • Container-title:Computer Networks
  • language:en
  • Short-container-title:Computer Networks

Author:

Gedikli Ahmet MelihORCID,Koseoglu MehmetORCID,Sen SevilORCID

Publisher

Elsevier BV

Subject

Computer Networks and Communications

Reference50 articles.

1. M2M service platforms: Survey, issues, and enabling technologies;Kim;IEEE Commun. Surv. Tutor.,2014

2. Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025 (in billions),2019

3. Cisco visual networking index: Forecast and trends, 2017–2022 white paper;Cisco,2019

4. 5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications;Wunder;IEEE Commun. Mag.,2014

5. D2.2 draft overall 5G RAN design;Marsch,2016

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1. Network Slicing-Based Learning Techniques for IoV in 5G and Beyond Networks;IEEE Communications Surveys & Tutorials;2024

2. A novel duplex deep reinforcement learning based RRM framework for next-generation V2X communication networks;Expert Systems with Applications;2023-12

3. Intelligent Preamble Allocation for 5G RAN Slicing: A Hierarchical Reinforcement Learning Based Approach;2023 IEEE 23rd International Conference on Communication Technology (ICCT);2023-10-20

4. Intelligent preamble allocation for coexistence of mMTC/URLLC devices: A hierarchical Q-learning based approach;China Communications;2023-08

5. Dynamic MAC Scheduling in O-RAN using Federated Deep Reinforcement Learning;2023 International Conference on Smart Applications, Communications and Networking (SmartNets);2023-07-25
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