Dynamic Spectrum Access for Internet-of-Things Based on Federated Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Dynamic Spectrum Access for Internet-of-Things Based on Federated Deep Reinforcement Learning

Published:2022-07 Issue:7 Volume:71 Page:7952-7956
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Li Feng¹^ORCID,Shen Bowen¹,Guo Jiale²^ORCID,Lam Kwok-Yan²^ORCID,Wei Guiyi¹^ORCID,Wang Li³

Affiliation:

1. School of Information and Electronic Engineering, Zhejiang Gongshang University, Hangzhou, China

2. School of Computer Science and Engineering, Nanyang Technological University, Singapore

3. College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China

Funder

National Research Foundation Singapore

Strategic Capability Research Centres Funding Initiative any opinions

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/9830787/09760286.pdf?arnumber=9760286

Reference14 articles.

1. HCP: Heterogeneous Computing Platform for Federated Learning Based Collaborative Content Caching Towards 6G Networks

2. ANT-Centric IoT Security Reference Architecture – Security-by-Design for Satellite-Enabled Smart Cities

3. Multi-Agent Deep Reinforcement Learning for Massive Access in 5G and Beyond Ultra-Dense NOMA System

4. Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and CR

5. Federated learning of deep networks using model averaging;mcmahan,2016

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2. Counterfactual Reward Estimation for Credit Assignment in Multi-agent Deep Reinforcement Learning over Wireless Video Transmission;2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS);2024-07-23

3. Dynamic Spectrum Optimization for Internet-of-Vehicles with Deep-Learning-Based Mobility Prediction;Wireless Personal Communications;2024-07

4. Blockchain-Enabled Federated Reinforcement Learning (B-FRL) Model for Privacy Preservation Service in IoT Systems;Wireless Personal Communications;2024-06

5. Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission;Frontiers of Information Technology & Electronic Engineering;2024-04-18

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