6 citations · 6 across the 9 of their papers we have counts for
9 papers
Flexible Intelligent Metasurface-Aided ISAC: User Fairness Optimization and Performance Evaluation
Hailun Huang, Yuwen Cao, Jiguang He +1
This paper investigates max-min user fairness optimization for flexible intelligent metasurface (FIM) and non-orthogonal multiple access (NOMA)-assisted integrated sensing and comm…
RePos: Relative-to-Absolute Pose Factorization for Cross-Environment WiFi-Based 3D Human Pose Estimation
Zhangcheng Hou, Tomoaki Ohtsuki
Device-free 3D human pose estimation from commodity WiFi Channel State Information (CSI) enables human sensing that preserves privacy and tolerates poor illumination, but its deplo…
mmGAT: Pose Estimation by Graph Attention with Mutual Features from mmWave Radar Point Cloud
Abdullah Al Masud, Shi Xintong, Mondher Bouazizi +1
Pose estimation and human action recognition (HAR) are pivotal technologies spanning various domains. While the image-based pose estimation and HAR are widely admired for their sup…
Generative Model-Aided Continual Learning for CSI Feedback in FDD mMIMO-OFDM Systems
Guijun Liu, Yuwen Cao, Tomoaki Ohtsuki +2
Deep autoencoder (DAE) frameworks have demonstrated their effectiveness in reducing channel state information (CSI) feedback overhead in massive multiple-input multiple-output (mMI…
A Deep Transfer Learning-Based Low-overhead Beam Prediction in Vehicle Communications
Zhiqiang Xiao, Yuwen Cao, Mondher Bouazizi +2
Existing transfer learning-based beam prediction approaches primarily rely on simple fine-tuning. When there is a significant difference in data distribution between the target dom…
Distributed Gossip-GAN for Low-overhead CSI Feedback Training in FDD mMIMO-OFDM Systems
Yuwen Cao, Guijun Liu, Tomoaki Ohtsuki +2
The deep autoencoder (DAE) framework has turned out to be efficient in reducing the channel state information (CSI) feedback overhead in massive multiple-input multipleoutput (mMIM…
Coverage and Rate Performance Analysis of Multi-RIS-Assisted Dual-Hop mmWave Networks
Yuwen Cao, Xiaowen Wu, Jiguang He +2
Millimeter-wave (mmWave) communication, which operates at high frequencies, has gained extensive research interest due to its significantly wide spectrum and short wavelengths. How…
Memristor-Based Meta-Learning for Fast mmWave Beam Prediction in Non-Stationary Environments
Yuwen Cao, Tomoaki Ohtsuki, Setareh Maghsudi +1
Traditional machine learning techniques have achieved great success in improving data-rate performance and reducing latency in millimeter wave (mmWave) communications. However, the…
Energy Efficient Transmission Parameters Selection Method Using Reinforcement Learning in Distributed LoRa Networks
Ryotai Airiyoshi, Mikio Hasegawa, Tomoaki Ohtsuki +1
With the increase in demand for Internet of Things (IoT) applications, the number of IoT devices has drastically grown, making spectrum resources seriously insufficient. Transmissi…