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Ying-Chang Liang

Researcher at University of Electronic Science and Technology of China

Publications -  718
Citations -  37349

Ying-Chang Liang is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Cognitive radio & Communication channel. The author has an hindex of 90, co-authored 673 publications receiving 32651 citations. Previous affiliations of Ying-Chang Liang include Tsinghua University & University of Maryland, College Park.

Papers
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Sensing-Throughput Tradeoff for Cognitive Radio Networks

TL;DR: This paper designs the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected, and forms the sensing-throughput tradeoff problem mathematically, and uses energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput.
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Eigenvalue-based spectrum sensing algorithms for cognitive radio

TL;DR: New sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users can be used for various signal detection applications without requiring the knowledge of signal, channel and noise power.
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Eigenvalue based Spectrum Sensing Algorithms for Cognitive Radio

TL;DR: In this article, the eigenvalues of the covariance matrix of signals received at the secondary users are used for signal detection in cognitive radio systems, and the proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated.
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Cognitive radio networking and communications: an overview

TL;DR: This paper provides a systematic overview on CR networking and communications by looking at the key functions of the physical, medium access control (MAC), and network layers involved in a CR design and how these layers are crossly related.
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Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

TL;DR: Simulation results show that even under stringent interference-power constraints, substantial capacity gains are achievable for the secondary transmission by employing multi-antennas at the secondary transmitter, even when the number of primary receivers exceeds that of secondary transmit antennas in a CR network.