Hsin-Yuan Chang

Orcid: 0000-0001-6603-6020

According to our database1, Hsin-Yuan Chang authored at least 16 papers between 2017 and 2025.

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

Timeline

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Bibliography

2025
Frequency Estimation of Vital Sign Signals Using FMCW Radar: A Cramer-Rao Lower Bound Analysis and Experimental Validation.
IEEE Trans. Instrum. Meas., 2025

Worst-Case MSE Minimization for RIS-Assisted mmWave MU-MISO Systems with Hardware Impairments and Imperfect CSI.
Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025

2024
Deep Unfolded Hybrid Beamforming in Reconfigurable Intelligent Surface Aided mmWave MIMO-OFDM Systems.
IEEE Wirel. Commun. Lett., April, 2024

A Self-Supervised Approach for Cooperative Neighboring Vehicle Positioning System based on Spatial-Temporal Learning Techniques.
Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

2023
Hybrid Beamforming for Dual-Functional Radar-Communication Systems.
Proceedings of the 97th IEEE Vehicular Technology Conference, 2023

Wireless Multi-Target Vital Sign Detection Using SIMO-FMCW Radar in Multipath Propagation Environments.
Proceedings of the 97th IEEE Vehicular Technology Conference, 2023

Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications.
Proceedings of the 97th IEEE Vehicular Technology Conference, 2023

2022
Super Resolution-Based Beam Selection With Hierarchical Codebook in mmWave Communication.
IEEE Wirel. Commun. Lett., 2022

Hybrid Beamforming in mmWave MIMO-OFDM Systems via Deep Unfolding.
Proceedings of the 95th IEEE Vehicular Technology Conference, 2022

Fast Acquisition and Accurate Vital Sign Estimation with Deep Learning-Aided Weighted Scheme Using FMCW Radar.
Proceedings of the 95th IEEE Vehicular Technology Conference, 2022

Unsupervised Learning Based Hybrid Beamforming with Low-Resolution Phase Shifters for MU-MIMO Systems.
Proceedings of the IEEE International Conference on Communications, 2022

Cooperative Neighboring Vehicle Positioning Systems Based on Graph Convolutional Network: A Multi-Scenario Transfer Learning Approach.
Proceedings of the IEEE International Conference on Communications, 2022

RangeSRN: Range Super-Resolution Network Using mmWave FMCW Radar.
Proceedings of the IEEE Global Communications Conference, 2022

2021
GCN-CNVPS: Novel Method for Cooperative Neighboring Vehicle Positioning System Based on Graph Convolution Network.
IEEE Access, 2021

2020
DL-Aided NOMP: a Deep Learning-Based Vital Sign Estimating Scheme Using FMCW Radar.
Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

2017
Using Machine Learning to Forecast Patent Quality - Take "Vehicle Networking" Industry for Example.
Proceedings of the Transdisciplinary Engineering: A Paradigm Shift, 2017


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