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Data-Driven Orchestration for Distributed RAN Intelligent Controller Placement in 6G Networks

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BORIS DOI
10.48620/78477
Date of Publication
2024
Publication Type
Conference Paper
Division/Institute

Institute of Computer...

Author
Hashemi Nezhad, Elham
Institute of Computer Science
Di Maio, Antonioorcid-logo
Institute of Computer Science
Braun, Torstenorcid-logo
Institute of Computer Science
Institute of Computer Science, Communication and Distributed Systems (CDS)
Language
English
Description
Open-Radio Access Network ( O-RAN ) brings an innovative approach to address the issues of controller placement in large-scale 6G networks. In this work, we introduce a Reinforcement Learning (RL ) algorithm for decentralized RAN Intelligent Controller Orchestration in 6G Networks, which leverages the online learning capabilities of a multi-agent RL system. Our method achieves around 42-66% lower user latency and 9-14% higher user packet delivery ratio compared to state-of-the-art baselines in a broad range of simulated scenarios.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/194060
Project(s)
Service-oriented 6G network architecture for distributed, intelligent, and sustainable cloud-native communication systems (6G-CLOUD)
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FileFile TypeFormatSizeLicensePublisher/Copright statementContent
Data_Driven_Orchestration_for_Distributed_RAN_Intelligent_Controller_Placement_in_6G_Networks.pdftextAdobe PDF987.14 KBpublished
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