most citedSpectrum Sensing for Cognitive Radio Using Kernel-Based Learning

17 citations · 39 across the 7 of their papers we have counts for

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cs.IT2011

GLRT-Based Spectrum Sensing with Blindly Learned Feature under Rank-1 Assumption

Peng Zhang, Robert Qiu

Prior knowledge can improve the performance of spectrum sensing. Instead of using universal features as prior knowledge, we propose to blindly learn the localized feature at the se…

cs.IT20115 cited

Demonstration of Spectrum Sensing with Blindly Learned Feature

Peng Zhang, Robert Qiu, Nan Guo

Spectrum sensing is essential in cognitive radio. By defining leading \textit{eigenvector} as feature, we introduce a blind feature learning algorithm (FLA) and a feature template…

cs.IT20111 cited

Cooperative Wideband Spectrum Sensing for the Centralized Cognitive Radio Network

Peng Zhang, Robert Qiu

Various primary user (PU) radios have been allocated into fixed frequency bands in the whole spectrum. A cognitive radio network (CRN) should be able to perform the wideband spectr…

cs.IT20114 cited

Spectrum Sensing Based on Blindly Learned Signal Feature

Peng Zhang, Robert Qiu

Spectrum sensing is the major challenge in the cognitive radio (CR). We propose to learn local feature and use it as the prior knowledge to improve the detection performance. We de…

cs.IT20116 cited

Modified Orthogonal Matching Pursuit Algorithm for Cognitive Radio Wideband Spectrum Sensing

Peng Zhang, Robert Qiu

Sampling rate is the bottleneck for spectrum sensing over multi-GHz bandwidth. Recent progress in compressed sensing (CS) initialized several sub-Nyquist rate approaches to overcom…