A Comparative Analysis of Deep Reinforcement Learning-Based xApps in O-RAN
Author:
Affiliation:
1. Institute for the Wireless Internet of Things, Northeastern University,Boston,MA,U.S.A.
2. Dell Technologies, P&O OCTO - Advanced Wireless Technology
Funder
U.S. National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10436708/10436716/10437367.pdf?arnumber=10437367
Reference15 articles.
1. Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challenges
2. Self-play learning strategies for resource assignment in Open-RAN networks
3. ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms
4. OrchestRAN: Network Automation through Orchestrated Intelligence in the Open RAN
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1. Developing Trustworthy Reinforcement Learning Applications for Next-Generation Open Radio Access Networks;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06
2. Misconfiguration in O-RAN: Analysis of the impact of AI/ML;Computer Networks;2024-06
3. DRL-Based Latency-Aware Network Slicing in O-RAN with Time-Varying SLAs;2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19
4. Colosseum: The Open RAN Digital Twin;IEEE Open Journal of the Communications Society;2024
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