Using Deep Reinforcement Learning for mmWave Real-Time Scheduling
Author:
Affiliation:
1. Technion,CS Dept,Israel
2. Ceragon Ltd
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10302728/10302750/10302794.pdf?arnumber=10302794
Reference33 articles.
1. Reinforcement Learning for Multi-Hop Scheduling and Routing of Real-Time Flows;hasanzadezonuzy;Int Symp on Modeling and Optimization in Mobile Ad Hoc and Wireless Networks (WiOPT),2020
2. A Reinforcement Learning Approach for Scheduling in mmWave Networks
3. Radio Resource Scheduling for 5G NR via Deep Deterministic Policy Gradient
4. DRL-Based Channel and Latency Aware Radio Resource Allocation for 5G Service-Oriented RoF-MmWave RAN
5. Stable-Baselines3: Reliable Reinforcement Learning Implementations;raffin;Journal of Machine Learning Research,2021
Cited by 1 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. Flexible Reinforcement Learning Scheduler for 5G Networks;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05
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