Yijing Liu

Orcid: 0000-0003-3079-5919

Affiliations:
  • University of Electronic Science and Technology of China, UESTC, Yangtze Delta Region Institute, National Key Laboratory of Science and Technology on Communications, Chengdu, China


According to our database1, Yijing Liu authored at least 26 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
BIO-SD: A Blockchain-Empowered Intelligent Resource Management for Symbiotic Devices.
IEEE Trans. Veh. Technol., May, 2024

Joint UAV Deployment and Resource Allocation: A Personalized Federated Deep Reinforcement Learning Approach.
IEEE Trans. Veh. Technol., March, 2024

Generative AI in Data Center Networking: Fundamentals, Perspectives, and Case Study.
CoRR, 2024

Straggler-Aware Federated Learning Based on Adaptive Clustering to Support Edge Intelligence.
Proceedings of the IEEE International Conference on Communications, 2024

2023
Toward Secure Data Storage in Web 3.0: Ciphertext-Policy Attribute-Based Encryption.
IEEE Netw., November, 2023

A Unified Framework for Joint Sensing and Communication in Resource Constrained Mobile Edge Networks.
IEEE Trans. Mob. Comput., October, 2023

Slicing4Meta: An Intelligent Integration Architecture with Multi-Dimensional Network Resources for Metaverse-as-a-Service in Web 3.0.
IEEE Commun. Mag., August, 2023

Ensemble Distillation Based Adaptive Quantization for Supporting Federated Learning in Wireless Networks.
IEEE Trans. Wirel. Commun., June, 2023

Joint Sensing, Communication, and Computation in Mobile Crowdsensing Enabled Edge Networks.
IEEE Trans. Wirel. Commun., April, 2023

Beam Management in Ultra-Dense mmWave Network via Federated Reinforcement Learning: An Intelligent and Secure Approach.
IEEE Trans. Cogn. Commun. Netw., February, 2023

Joint Multi-UAV Deployment and Resource Allocation Based on Personalized Federated Deep Reinforcement Learning.
Proceedings of the IEEE International Conference on Communications, 2023

Intelligent Beam Configuration for Neighbor Discovery in Ad Hoc Networks with Directional Antennas.
Proceedings of the IEEE International Conference on Communications, 2023

Intelligent Resource Management in Symbiotic Radio under a Trusted Coevolution.
Proceedings of the IEEE International Conference on Communications, 2023

2022
Resource Consumption for Supporting Federated Learning in Wireless Networks.
IEEE Trans. Wirel. Commun., 2022

Blockchain-Empowered Federated Learning Approach for an Intelligent and Reliable D2D Caching Scheme.
IEEE Internet Things J., 2022

Slicing4Meta: An Intelligent Integration Framework with Multi-dimensional Network Resources for Metaverse-as-a-Service in Web 3.0.
CoRR, 2022

Resource Consumption for Supporting Federated Learning Enabled Network Edge Intelligence.
Proceedings of the 2022 IEEE International Conference on Communications Workshops, 2022

Adaptive Quantization based on Ensemble Distillation to Support FL enabled Edge Intelligence.
Proceedings of the IEEE Global Communications Conference, 2022

Cooperative Date Sensing, Communication and Computation in Resource Constrained Mobile Crowdsensing.
Proceedings of the IEEE Global Communications Conference, 2022

A Joint Sensing and Communication Framework in Resource Constrained Mobile Edge Networks.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Access Control for RAN Slicing based on Federated Deep Reinforcement Learning.
Proceedings of the ICC 2021, 2021

A Privacy-preserved D2D Caching Scheme Underpinned by Blockchain-enabled Federated Learning.
Proceedings of the IEEE Global Communications Conference, 2021

2020
Device Association for RAN Slicing Based on Hybrid Federated Deep Reinforcement Learning.
IEEE Trans. Veh. Technol., 2020

Virtual Network Function Deployment Strategy in Clustered Multi-Mobile Edge Clouds.
Proceedings of the 2020 IEEE Wireless Communications and Networking Conference, 2020

Network Function Migration in Softwarization Based Networks with Mobile Edge Computing.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019
Multi-Agent Reinforcement Learning Based Cooperative Content Caching for Mobile Edge Networks.
IEEE Access, 2019


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