Load Balancing for Communication Networks via Data-Efficient Deep Reinforcement Learning

Author:

Wu Di1,Kang Jikun1,Xu Yi Tian1,Li Hang1,Li Jimmy1,Chen Xi1,Rivkin Dmitriy1,Jenkin Michael1,Lee Taeseop2,Park Intaik2,Liu Xue1,Dudek Gregory1

Affiliation:

1. Samsung Electronics,Canada

2. Samsung Electronics,Korea (South)

Publisher

IEEE

Cited by 7 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. Learning to Adapt: Communication Load Balancing via Adaptive Deep Reinforcement Learning;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

2. Multi-Agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks;ICC 2023 - IEEE International Conference on Communications;2023-05-28

3. Learning-Based Model Predictive Control for User Association in Multi-Band Mobile Networks;ICC 2023 - IEEE International Conference on Communications;2023-05-28

4. Communication Load Balancing via Efficient Inverse Reinforcement Learning;ICC 2023 - IEEE International Conference on Communications;2023-05-28

5. Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios;ICC 2023 - IEEE International Conference on Communications;2023-05-28

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