Published in IEEE TPAMI, 2026
In this paper, we propose WiAnchor, a novel training framework for efficient cross-domain adaptation, and NFS-Fi, a multi-person near-field sensing dataset. Code
Published in ACM MobiCom, 2025
This study leverages multi-link receiver to expand the effective sensing bandwidth. Code
Published in ACM MobiCom, 2025
This study leverages poisoning attacks to protect user privacy. Code
Published in IEEE JSAC, 2025
This study establishes a theoretical framework for recovering wideband signals from sparse channel samples.
Published in IEEE INFOCOM 2025, 2025
This study theoretically explains the generation of wideband signals using discrete channel samples.
Published in IEEE Transactions on Mobile Computing, 2025
This study applies channel hopping sensing and nearfield sensing to VR devices.
Published in IEEE Transactions on Instrumentation and Measurement, 2024
This study proposes a data-driven optimization strategy for constructing the optimal microphone array configuration in-vehicle environments.
Published in ACM MobiCom, 2024
The core idea of BeamCraft involves corrupting beamforming decisions by injecting crafted BFIs that feed an access point (AP) with erroneous information on channel states. Code
Published in IEEE Wireless Communications Letters, 2024
In this letter, we first derive a mathematical model of BFI, characterizing its relationship with CSI explicitly, and then develop a closed-form expression of BFI for 2×2 MIMO systems. To enhance the efficiency of BFI-based sensing by selecting only the most informative features, we quantify the sensing capacity of BFI using the Cramer-Rao bound (CRB) and then propose an efficient CRB-based BFI feature selection algorithm.
Published in ACM MobiSys, 2024
We propose UWB-Fi as a novel Wi-Fi sensing system with ultra-wide bandwidth, leveraging only discrete and irregular channel sampling. Code
Published in Applied Soft Computing, 2022
This paper aims to develop an accurate and efficient end-to-end fault detection model trained by small-scale data for the rotating machinery.
Published in IEEE Sensors Journal, 2022
An echo state network with improved topology (IESN) is proposed for accurate and efficient time series prediction.
Published in SAE Technical Paper, 2020
This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN).
Published in Measurement, 2019
Combined with recursive model and energy difference tracking method, the optimized VMD can decompose signals into several modes based on stop criterion instead of artificial values set in advance.