Deep Reinforcement Learning for Multi-Functional RIS-Aided Over-the-Air Federated Learning in Internet of Robotic Things-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning for Multi-Functional RIS-Aided Over-the-Air Federated Learning in Internet of Robotic Things

Published:2024-06-09 Issue: Volume: Page:5461-5466
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Zhang Xinran¹,Tian Hui¹,Ni Wanli²,Yang Zhaohui³

Affiliation:

1. Beijing University of Posts and Telecommunications,State Key laboratory of Networking and Switching Technology,Beijing,China,100876

2. Tsinghua University,Department of Electronic Engineering,Beijing,China,100084

3. Zhejiang Lab,Hangzhou,China,311121

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622931.pdf?arnumber=10622931

Reference15 articles.

1. The Internet of Robotic Things

2. Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

3. Deep Reinforcement Learning for Energy Efficiency Maximization in SWIPT-Based Over-the-Air Federated Learning

4. Federated Learning in Multi-RIS Aided Systems

5. Federated Deep Reinforcement Learning for RIS-Assisted Indoor Multi-Robot Communication Systems

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