most citedSpectrum Sensing for Cognitive Radio Using Kernel-Based Learning

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

collaborators

7 papers

cs.NI20116 cited

SVM and Dimensionality Reduction in Cognitive Radio with Experimental Validation

Shujie Hou, Robert C. Qiu, Zhe Chen +1

There is a trend of applying machine learning algorithms to cognitive radio. One fundamental open problem is to determine how and where these algorithms are useful in a cognitive r…

cs.NI201117 cited

Spectrum Sensing for Cognitive Radio Using Kernel-Based Learning

Shujie Hou, Robert C. Qiu

Kernel method is a very powerful tool in machine learning. The trick of kernel has been effectively and extensively applied in many areas of machine learning, such as support vecto…

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…