Data-Driven Orchestration for Distributed RAN Intelligent Controller Placement in 6G Networks
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BORIS DOI
Date of Publication
2024
Publication Type
Conference Paper
Division/Institute
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.
File(s)
File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
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Data_Driven_Orchestration_for_Distributed_RAN_Intelligent_Controller_Placement_in_6G_Networks.pdf | text | Adobe PDF | 987.14 KB | published |