Yixuan Zou

Orcid: 0000-0002-6422-480X

According to our database1, Yixuan Zou authored at least 16 papers between 2019 and 2024.

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

Timeline

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Links

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Bibliography

2024
Wideband Beamforming for RIS Assisted Near-Field Communications.
CoRR, 2024

2023
UDGAN: A new urban design inspiration approach driven by using generative adversarial networks.
J. Comput. Des. Eng., December, 2023

Exploiting NOMA and RIS in Integrated Sensing and Communication.
IEEE Trans. Veh. Technol., October, 2023

Machine Learning in RIS-Assisted NOMA IoT Networks.
IEEE Internet Things J., 2023

Resource allocation for multiple RISs assisted NOMA empowered D2D communication: A MAMP-DQN approach.
Ad Hoc Networks, 2023

Adaptive NGMA Scheme for IoT Networks: A Deep Reinforcement Learning Approach.
Proceedings of the IEEE International Conference on Communications, 2023

Near-Field Wideband Beamfocusing Optimization: A Heuristic Two-Stage Approach.
Proceedings of the IEEE Global Communications Conference, 2023

STARS for Spectral Efficiency in Wideband Terahertz Communications.
Proceedings of the IEEE Global Communications Conference, 2023

2022
The Influence of E-learning Behavior on Students' Learning Performance of Disaster Emergency Knowledge.
Int. J. Emerg. Technol. Learn., 2022

Reconfigurable Intelligence Surface Aided UAV-MEC Systems With NOMA.
IEEE Commun. Lett., 2022

Multi-objective Optimization of Energy and Latency in URLLC-enabled Wireless VR Networks.
Proceedings of the 18th International Symposium on Wireless Communication Systems, 2022

DRL-based Energy Efficient Resource Allocation for STAR-RIS Assisted Coordinated Multi-cell Networks.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Joint User Activity and Data Detection in Grant-Free NOMA using Generative Neural Networks.
Proceedings of the ICC 2021, 2021

Meta-learning for RIS-assisted NOMA Networks.
Proceedings of the IEEE Global Communications Conference, 2021

2020
Preliminary Study on Deep-learning for Retinal Vessels Segmentation.
Proceedings of the 15th International Conference on Computer Science & Education, 2020

2019
U-GAN: Generative Adversarial Networks with U-Net for Retinal Vessel Segmentation.
Proceedings of the 14th International Conference on Computer Science & Education, 2019


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