Yingpei Lin

A Novel Spectrum-Sensing Technique in Cognitive Radio Based on Stochastic Resonance

We propose a novel spectrum-sensing method for cognitive radio (CR) based on stochastic resonance (SR). The spectral power of primary users (PUs) can be amplified, and the signal-to-noise ratio (SNR) of a received signal can be increased using SR. This ensures that the detection probability of the proposed approach is higher than that of the traditional energy detector. The detection probability of the proposed method is also theoretically derived under a constant false-alarm rate (CFAR). Performance analyses and computer simulation results show that the effectiveness of the proposed SR-based spectrum-sensing approach, particularly under low SNR circumstances, is better than that of the traditional energy-detection method. The computational complexity of the proposed approach can also be guaranteed to be comparable with the traditional spectrum-sensing methods.

A Cyclostationary-Based Spectrum Sensing Method Using Stochastic Resonance in Cognitive Radio

A spectrum sensing approach based on the combination of cyclostationary feature detection (CFD) and stochastic resonance (SR) in cognitive radio (CR) is proposed in this paper. The SR technique can be used in the spectrum sensing based on CFD because the CFD method does not need to consider the distribution of the signals received by the secondary users. An improvement of the spectrum sensing performances can be conducted by the proposed method for its satisfaction of the Improvability of Detection via SR Theorem. Numerical results show that the proposed spectrum sensing scheme has better sensing performances than the conventional CFD method.

A Censoring Cooperative Spectrum Sensing Scheme Based on Stochastic Resonance in Cognitive Radio

A new censoring cooperative spectrum sensing scheme in cognitive radio (CR) network is proposed in this paper, which is based on stochastic resonance (SR) technique and optimal censoring interval. The selection strategy for the optimal censoring interval is derived. The observations of the cooperative secondary users (SUs) whose statistics fall into the censoring interval are processed by SR system. Theoretical analyses and simulation results show that the proposed cooperative spectrum sensing scheme has the same detection performance and lower computational complexity compared with the method that each cooperative performs spectrum sensing using SR-based energy detection, and the detection performance of both above method is superior than that of the conventional method that each cooperative performs spectrum sensing using energy detection.

Spectrum Sensing Approach Based on Optimal Stochastic Resonance Technique under Color Noise Background in Cognitive Radio Networks

An optimal-stochastic-resonance-based spectrum sensing approach under color noise environment is proposed in this paper. It can improve the detection performance of energy detector in color noise background especially under low signal-to-noise radio (SNR). The suitable stochastic resonance (SR) noise and corresponding driving parameter can be introduced to maximize the output SNR of the SR system and the received signal. Computer simulation results show the efficiency of the proposed spectrum sensing approach under different kinds of color noises and its advantages over traditional energy detectors.

A spectrum sensing method in cognitive radio based on the third order cyclic cumulant

A spectrum sensing method in cognitive radio (CR) based on the third order cyclic cumulant (TOCC) according to the third order cyclostationarity of the most primary user (PU) signals is proposed in this paper. The binary hypothesis test model and the test statistic are constructed and the explicit formula of the detection probability under a constant false alarm rate (CFAR) is derived exploiting the asymptotic optimal estimation theory. The computational complexity can be decreased greatly by the improved algorithm. Simulation results are presented to illustrate the superior detection performances of the proposed spectrum sensing scheme.

Cooperative spectrum sensing based on stochastic resonance in cognitive radio networks

A new censoring cooperative spectrum sensing scheme based on stochastic resonance (SR) technique in cognitive radio (CR) network is proposed in this paper. The observations of the cooperative secondary users (SUs) whose statistics fall into the censoring interval are processed by SR system in the proposed scheme. The hard fusion and the soft fusion for the censoring cooperative spectrum sensing scheme are analyzed respectively. Theoretical analyses and simulation results show that the proposed censoring cooperative spectrum sensing scheme has the same detection performance as and lower computational complexity than the method that each cooperative SU performs spectrum sensing using SR-based energy detection, and its detection performance is superior to that of the conventional method that all the cooperative SUs perform spectrum sensing using energy detection in hard fusion. In soft fusion, the proposed censoring cooperative spectrum sensing based on equal gain combination can achieve the optimal sensing performance approximately.