5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-Based Integrated Access and Backhaul-Reference-Cited by-同舟云学术

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5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-Based Integrated Access and Backhaul

Published:2024 Issue: Volume:2 Page:1109-1126
ISSN:2831-316X
Container-title:IEEE Transactions on Machine Learning in Communications and Networking
language:
Short-container-title:Trans. Mach. Learn. Comm. Netw.

Author:

Zhang Hongyi¹^ORCID,Qi Zhiqiang²^ORCID,Li Jingya²^ORCID,Aronsson Anders²,Bosch Jan¹^ORCID,Holmström Olsson Helena³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden

2. Ericsson Research, Ericsson, Stockholm, Sweden

3. Department of Computer Science and Media Technology, Malmö University, Malmö, Sweden

Funder

Chalmers AI Research Center and Software Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/9882533/10356147/10634545.pdf?arnumber=10634545

Reference51 articles.

1. Cell on Wheels-Unmanned Aerial Vehicle System for Providing Wireless Coverage in Emergency Situations

2. Wireless communications with unmanned aerial vehicles: opportunities and challenges

3. Towards providing connectivity when and where it counts: An overview of deployable 5G networks;Li;arXiv:2110.05360,2021

4. Deployable Networks for Public Safety in 5G and Beyond: A Coverage and Interference Study

5. Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

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