Tiago Koketsu Rodrigues

Orcid: 0000-0003-0881-3818

Affiliations:
  • Tohoku University, Sendai, Miyagi, Japan


According to our database1, Tiago Koketsu Rodrigues authored at least 20 papers between 2019 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Five Disruptive Technologies in 6G to Support Digital Twin Networks.
IEEE Wirel. Commun., February, 2024

2023
Hybrid Centralized and Distributed Learning for MEC-Equipped Satellite 6G Networks.
IEEE J. Sel. Areas Commun., April, 2023

Quantum Multiagent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems.
IEEE Internet Things J., 2023

A Survey on Multi-AP Coordination Approaches over Emerging WLANs: Future Directions and Open Challenges.
CoRR, 2023

Smart Handover with Predicted User Behavior using Convolutional Neural Networks for WiGig Systems.
CoRR, 2023

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems.
CoRR, 2023

Impact of UAV Failure and Severe Weather Conditions in mmWave and Terahertz Signals for AeriaL Edge Computing.
Proceedings of the 98th IEEE Vehicular Technology Conference, 2023

Robust Deep Learning-based Indoor mmWave Channel Prediction Under Concept Drift.
Proceedings of the 98th IEEE Vehicular Technology Conference, 2023

2022
Network Slicing with Centralized and Distributed Reinforcement Learning for Combined Satellite/Ground Networks in a 6G Environment.
IEEE Wirel. Commun., 2022

Offloading Decision for Mobile Multi-Access Edge Computing in a Multi-Tiered 6G Network.
IEEE Trans. Emerg. Top. Comput., 2022

Survey on Digital Twin Edge Networks (DITEN) Toward 6G.
IEEE Open J. Commun. Soc., 2022

Robust Multiuser Beamforming for IRS-Enhanced Near-Space Downlink Communications Coexisting With Satellite System.
IEEE Internet Things J., 2022

Deep Q Networks with Centralized Learning over LEO Satellite Networks in a 6G Cloud Environment.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Deep Learning Techniques for Advancing 6G Communications in the Physical Layer.
IEEE Wirel. Commun., 2021

Edge Cloud Server Deployment With Transmission Power Control Through Machine Learning for 6G Internet of Things.
IEEE Trans. Emerg. Top. Comput., 2021

Envisioning Intelligent Reflecting Surface Empowered Space-Air-Ground Integrated Network.
IEEE Netw., 2021

Application of Cybertwin for Offloading in Mobile Multiaccess Edge Computing for 6G Networks.
IEEE Internet Things J., 2021

2020
Machine Learning Meets Computation and Communication Control in Evolving Edge and Cloud: Challenges and Future Perspective.
IEEE Commun. Surv. Tutorials, 2020

Prediction of Network Traffic Load on High Variability Data Based on Distance Correlation.
Proceedings of the 92nd IEEE Vehicular Technology Conference, 2020

2019
Hyperparameter Study of Machine Learning Solutions for the Edge Server Deployment Problem.
Proceedings of the 90th IEEE Vehicular Technology Conference, 2019


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