Dynamic User-Scheduling and Power Allocation for SWIPT Aided Federated Learning: A Deep Learning Approach-Reference-Cited by-同舟云学术

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Dynamic User-Scheduling and Power Allocation for SWIPT Aided Federated Learning: A Deep Learning Approach

Published:2022 Issue: Volume: Page:1-14
ISSN:1536-1233
Container-title:IEEE Transactions on Mobile Computing
language:
Short-container-title:IEEE Trans. on Mobile Comput.

Author:

Li Yang¹^ORCID,Wu Yuan¹^ORCID,Song Yuxiao¹^ORCID,Qian Liping²,Jia Weijia³^ORCID

Affiliation:

1. State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China

2. College of Information Engineering, Zhejiang University of Technology, Hangzhou, China

3. Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Software

Link

http://xplorestaging.ieee.org/ielx7/7755/4358975/09866823.pdf?arnumber=9866823

Cited by 7 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. Convergence Analysis and Optimization of SWIPT-Based Over-the-Air Federated Learning;IEEE Communications Letters;2024-06

2. Delay Minimization of Federated Learning Over Wireless Powered Communication Networks;IEEE Communications Letters;2024-01

3. Distributed Joint Resource Optimization for Federated Learning Task Distribution;IEEE Transactions on Green Communications and Networking;2023-09

4. Enabling Fully-Decoupled Radio Access With Elastic Resource Allocation;IEEE Transactions on Cognitive Communications and Networking;2023-08

5. Wireless Federated Learning With Hybrid Local and Centralized Training: A Latency Minimization Design;IEEE Journal of Selected Topics in Signal Processing;2023-01

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