12 papers
UAV-Assisted Cooperative Edge Inference for Low-Altitude Economy via MoE-based Hierarchical Deep Reinforcement Learning
Wenhao Zhuang, Yuyi Mao, Ivan Wang-Hei Ho +1
The low-altitude economy (LAE) is reshaping the industrial landscape by deploying unmanned aerial vehicles (UAVs) to facilitate a wide range of applications demanding flexible aeri…
Scene-Adaptive Continual Learning for CSI-based Human Activity Recognition with Mixture of Experts
Wenhan Zheng, Yuyi Mao, Ivan Wang-Hei Ho
Channel state information (CSI)-based human activity recognition (HAR) is vulnerable to performance degradation under domain shifts across varying physical environments. Continual…
Energy-Efficient Velocity Profile Optimization for Movable Antenna-Enabled Sensing Systems
Jiannan Wang, Yuyi Mao, Xianghao Yu +1
Movable antennas (MAs) enable the reconfiguration of array geometry within a bounded region to exploit sub-wavelength spatial degrees of freedom in wireless communication and sensi…
FedAPA: Federated Learning with Adaptive Prototype Aggregation Toward Heterogeneous Wi-Fi CSI-based Crowd Counting
Jingtao Guo, Yuyi Mao, Ivan Wang-Hei Ho
Wi-Fi channel state information (CSI)-based sensing provides a non-invasive, device-free approach for tasks such as human activity recognition and crowd counting, but large-scale d…
Integrated Sensing and Communications for Low-Altitude Economy: A Deep Reinforcement Learning Approach
Xiaowen Ye, Yuyi Mao, Xianghao Yu +3
This paper studies an integrated sensing and communications (ISAC) system for low-altitude economy (LAE), where a ground base station (GBS) provides communication and navigation se…
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding
Wenhao Zhuang, Yuyi Mao
Mobile edge computing (MEC) has empowered mobile devices (MDs) in supporting artificial intelligence (AI) applications through collaborative efforts with proximal MEC servers. Unfo…
RSSI-Assisted CSI-Based Passenger Counting with Multiple Wi-Fi Receivers
Jingtao Guo, Wenhao Zhuang, Yuyi Mao +1
Passenger counting is crucial for public transport vehicle scheduling and traffic capacity evaluation. However, most existing methods are either costly or with low counting accurac…
UAV-Enabled Wireless Networks for Integrated Sensing and Learning-Oriented Communication
Wenhao Zhuang, Xinyu He, Yuyi Mao +1
Future wireless networks are envisioned to support both sensing and artificial intelligence (AI) services. However, conventional integrated sensing and communication (ISAC) network…
Energy-Efficient Channel Decoding for Wireless Federated Learning: Convergence Analysis and Adaptive Design
Linping Qu, Yuyi Mao, Shenghui Song +1
One of the most critical challenges for deploying distributed learning solutions, such as federated learning (FL), in wireless networks is the limited battery capacity of mobile cl…
Approximate Message Passing-Enhanced Graph Neural Network for OTFS Data Detection
Wenhao Zhuang, Yuyi Mao, Hengtao He +4
Orthogonal time frequency space (OTFS) modulation has emerged as a promising solution to support high-mobility wireless communications, for which, cost-effective data detectors are…
How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink Channels
Linping Qu, Shenghui Song, Chi-Ying Tsui +1
Because of its privacy-preserving capability, federated learning (FL) has attracted significant attention from both academia and industry. However, when being implemented over wire…
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao, Zijian Li, Wenqiang Sun +6
Federated learning (FL) has emerged as a secure paradigm for collaborative training among clients. Without data centralization, FL allows clients to share local information in a pr…