MADRL Based Scheduling for 5G and Beyond

Author:

Chang Hao-Hsuan1,Sree R.B.Sai2,Chen Hao1,Zhang Jianzhong1,Liu Lingjia2

Affiliation:

1. Samsung Research America,Standards and Mobility Innovation Lab,Dallas,TX,USA

2. Virginia Tech,Dept. of Electrical and Computer Engineering,Blacksburg,VA,USA

Publisher

IEEE

Reference19 articles.

1. Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach

2. The “echo state” approach to analysing and training recurrent neural networks-with an erratum note;jaeger;German National Research Center for Information Technology Tech Rep,2001

3. NR; Physical layer procedures for data;Technical Specification (TS) 38 214 3rd Generation Partnership Project (3GPP),2021

4. On the Asymptotic Optimality of the Gradient Scheduling Algorithm for Multiuser Throughput Allocation

5. Providing quality of service over a shared wireless link

Cited by 2 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. Qmix-Based Cross-Domain Transmission Routing for Time-Sensitive and Deterministic Networks;2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC);2023-09-25

2. Performance Evaluation of 5G Delay-Sensitive Single-Carrier Multi-User Downlink Scheduling;2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC);2023-09-05

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