Reinforcement Learning-Based Grant-Free Mode Selection for O-RAN Systems-Reference-Cited by-同舟云学术

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Reinforcement Learning-Based Grant-Free Mode Selection for O-RAN Systems

Published:2023-06-19 Issue: Volume: Page:
ISSN:
Container-title:2023 International Wireless Communications and Mobile Computing (IWCMC)
language:
Short-container-title:

Author:

Hsu Hao-Wei¹,Lin Yen-Chen¹,Huang Chih-Wei¹,Lin Phone²,Yang Shun-Ren³

Affiliation:

1. National Central University,Department of Communication Engineering,Taoyuan,Taiwan

2. National Taiwan University,Department of Computer Science and Information Engineering,Taiwan

3. National Tsing Hua University,Department of Computer Science and Institute of Communications Engineering,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10182387/10182368/10182990.pdf?arnumber=10182990

Reference13 articles.

1. Model-Free Ultra Reliable Low Latency Communication (URLLC): A Deep Reinforcement Learning Framework

2. Study on channel model for frequencies from 0.5 to 100 ghz, v16.1.0;3GPP,2019

3. 3GPP Standardized 5G Channel Model for IIoT Scenarios: A Survey

4. New radio physical layer abstraction for system-level simulations of 5g networks;lagen;ICC 2020 - 2020 IEEE International Conference on Communications (ICC),2020

5. Intelligent O-RAN for beyond 5G and 6G wireless networks;niknam;arXiv 2005 08374,2020

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. The Evolution of Mobile Network Operations: A Comprehensive Analysis of Open RAN Adoption;Computer Networks;2024-04

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