Federated Learning Enabled Link Scheduling in D2D Wireless Networks-Reference-Cited by-同舟云学术

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Federated Learning Enabled Link Scheduling in D2D Wireless Networks

Published:2024-01 Issue:1 Volume:13 Page:89-92
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Chen Tianrui¹^ORCID,Zhang Xinruo²^ORCID,You Minglei¹^ORCID,Zheng Gan³^ORCID,Lambotharan Sangarapillai⁴^ORCID

Affiliation:

1. Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, U.K.

2. School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.

3. School of Engineering, University of Warwick, Coventry, U.K.

4. Institute for Digital Technologies, Loughborough University, London, U.K.

Funder

Engineering and Physical Sciences Research Council, U.K.

Royal Society

ESA Project

Digital Nottingham Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10384452/10268986.pdf?arnumber=10268986

Reference12 articles.

1. Intelligent Device-to-Device Communication in the Internet of Things

2. FPLinQ: A cooperative spectrum sharing strategy for device-to-device communications

3. A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks

4. Spatial Deep Learning for Wireless Scheduling

5. Graph Embedding-Based Wireless Link Scheduling With Few Training Samples

Cited by 2 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. Density-based anti-clustering for scheduling D2D communications;Wireless Networks;2024-01-27

2. FeDRL-D2D: Federated Deep Reinforcement Learning- Empowered Resource Allocation Scheme for Energy Efficiency Maximization in D2D-Assisted 6G Networks;IEEE Access;2024

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