SAMUS: Slice-Aware Machine Learning-based Ultra-Reliable Scheduling

Author:

Bektas Caner,Overbeck Dennis,Wietfeld Christian

Funder

Ministry of Economic Affairs

Publisher

IEEE

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data-Driven Proactive Uplink Slicing Enabling Real-Time Control within an Open RAN Testbed;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20

2. Dynamic Resource Allocation Using Deep Reinforcement Learning for 6G Metaverse;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19

3. Exploring the Feasibility of Configured Grant for Vehicular Scenario;2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall);2023-10-10

4. Towards Open 6G: Experimental O-RAN Framework for Predictive Uplink Slicing;ICC 2023 - IEEE International Conference on Communications;2023-05-28

5. Reinforcement Learning Based Resource Allocation for Network Slices in O-RAN Midhaul;2023 IEEE 20th Consumer Communications & Networking Conference (CCNC);2023-01-08

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