Meta Reinforcement Learning for Resource Allocation in Aerial Active-RIS-Assisted Networks With Rate-Splitting Multiple Access-Reference-Cited by-同舟云学术

Meta Reinforcement Learning for Resource Allocation in Aerial Active-RIS-Assisted Networks With Rate-Splitting Multiple Access

Published:2024-08-01 Issue:15 Volume:11 Page:26366-26383
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Faramarzi Sajad¹^ORCID,Javadi Sepideh²^ORCID,Zeinali Farshad²^ORCID,Zarini Hosein³^ORCID,Mili Mohammad Robat⁴^ORCID,Bennis Mehdi⁴^ORCID,Li Yonghui⁵^ORCID,Wong Kai-Kit⁶^ORCID

Affiliation:

1. School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

2. Department of Computer and Electrical Engineering, Pasargad Institute for Advanced Innovative Solutions, Tehran, Iran

3. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

4. Department of Electrical Engineering, University of Oulu, Oulu, Finland

5. School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia

6. Department of Electronic and Electrical Engineering, University College London, London, WC, U.K.

Funder

Engineering and Physical Sciences Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10607832/10525206.pdf?arnumber=10525206

Reference54 articles.

1. Massive Access for 5G and Beyond

2. Joint Resource Allocation and Reflecting Design in IRS-UAV Communication Networks with SWIPT

3. User Scheduling and Trajectory Optimization for Energy-Efficient IRS-UAV Networks With SWIPT

4. Joint Communication and Trajectory Design for Intelligent Reflecting Surface Empowered UAV SWIPT Networks

5. Liquid State Machine-Empowered Reflection Tracking in RIS-Aided THz Communications