User-Centric Resource Allocation in FD-RAN: A Stepwise Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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User-Centric Resource Allocation in FD-RAN: A Stepwise Reinforcement Learning Approach

Published:2024-07-01 Issue:13 Volume:11 Page:24210-24221
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Chen Jiacheng¹^ORCID,Liu Jingbo²^ORCID,Zhou Haibo³^ORCID

Affiliation:

1. Department of Strategic and Advanced Interdisciplinary Research, Peng Cheng Laboratory, Shenzhen, China

2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

3. School of Electronic Science and Engineering, Nanjing University, Nanjing, China

Funder

National Natural Science Foundation Original Exploration Project of China

Natural Science Foundation of China

Innovation and Entrepreneurship of Jiangsu Province High-Level Talent Program

Summit of the Six Top Talents Program of Jiangsu Province

Major Key Project of PCL

Basic and Frontier Research Project of PCL

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10570342/10500813.pdf?arnumber=10500813

Reference36 articles.

1. A Fully-Decoupled RAN Architecture for 6G Inspired by Neurotransmission

2. Enabling Fully-Decoupled Radio Access With Elastic Resource Allocation

3. Optimizing User Association and Spectrum Allocation in HetNets: A Utility Perspective

4. Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

5. A Novel Approach for QoS-Aware Joint User Association, Resource Block and Discrete Power Allocation in HetNets

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