H
Husheng Li
Researcher at University of Tennessee
Publications - 315
Citations - 6622
Husheng Li is an academic researcher from University of Tennessee. The author has contributed to research in topics: Cognitive radio & Smart grid. The author has an hindex of 42, co-authored 282 publications receiving 5957 citations. Previous affiliations of Husheng Li include Sequans & Qualcomm.
Papers
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Journal ArticleDOI
Indoor Positioning Systems Based on Visible Light Communication: State of the Art
Junhai Luo,Liying Fan,Husheng Li +2 more
TL;DR: This paper surveys over 100 papers ranging from pioneering papers to the state-of-the-art in the field to present the positioning technology, and emphasizes and analyzes the accuracy of VLC-based-IPS in the experiment and simulation environments.
Journal ArticleDOI
Time Synchronization Attack in Smart Grid: Impact and Analysis
TL;DR: A novel Time Synchronization Attack (TSA) is proposed to attack the timing information in smart grid and the effectiveness of TSA is demonstrated for three applications of phasor measurement unit (PMU) in smartgrid, namely transmission line fault detection, voltage stability monitoring and event locationing.
Journal ArticleDOI
Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks
TL;DR: This work proposes two decoding approaches, one based on matrix completion and the other based on joint sparsity recovery, both of which allow exact recovery from incomplete reports and validate the effectiveness and robustness of these approaches.
Journal ArticleDOI
Multicast Routing for Decentralized Control of Cyber Physical Systems with an Application in Smart Grid
Husheng Li,Lifeng Lai,H.V. Poor +2 more
TL;DR: The challenges of uncertain destinations and multiple routing modes, which are significantly different from traditional data networks, are addressed by employing the theories of hybrid systems and linear matrix inequalities, thus forming a novel framework for studying the communication sub-system in cyber physical systems.
Proceedings ArticleDOI
Attack-proof collaborative spectrum sensing in cognitive radio networks
TL;DR: A malicious user detection algorithm is developed that calculates the suspicious level of secondary users based on their past reports, and the proposed trust value indicator can effectively differentiate honest and malicious secondary users.