Digital twin‐enabled deep reinforcement learning for joint scheduling of ultra‐reliable low latency communication and enhanced mobile broad band: A reliability‐guaranteed approach-Reference-Cited by-同舟云学术

Digital twin‐enabled deep reinforcement learning for joint scheduling of ultra‐reliable low latency communication and enhanced mobile broad band: A reliability‐guaranteed approach

Published:2022-12-11 Issue:3 Volume:34 Page:
ISSN:2161-3915
Container-title:Transactions on Emerging Telecommunications Technologies
language:en
Short-container-title:Trans Emerging Tel Tech

Author:

Zhang Yining¹,Zhang Hengsheng²,Liu Xiaokai³,Zhao Chenglin¹⁴,Xu Fangmin¹⁴

Affiliation:

1. School of Artificial IntelligenceBeijing University of Posts and Telecommunications Beijing China

2. China Academy of Information and Communications Technology Beijing China

3. School of Electronic EngineeringBeijing University of Posts and Telecommunications Beijing China

4. School of Information and Communication EngineeringBeijing University of Posts and Telecommunications Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ett.4705

Reference23 articles.

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5. Intelligent Resource Slicing for eMBB and URLLC Coexistence in 5G and Beyond: A Deep Reinforcement Learning Based Approach