In this paper, a novel detection criterion is proposed to decide whether primary user(PU) exists based on joint analysis of the variance and correlation for observation signal,considering a correlation within the obse...In this paper, a novel detection criterion is proposed to decide whether primary user(PU) exists based on joint analysis of the variance and correlation for observation signal,considering a correlation within the observed signal. Simultaneously, the corresponding detection thresholds are also designed. Simulation experiments verify the proposed method suits for the observation signal in Additive White Gaussian Noise(AWGN), Rayleigh,Rician channel and the detection performance is improved greatly.展开更多
As a crucial component in Cognitive Radio(CR) networks, spectrum sensing has been attracting lots of attention. Some conventional methods for spectrum sensing are sensitive to uncertain signal and noise, its applicabi...As a crucial component in Cognitive Radio(CR) networks, spectrum sensing has been attracting lots of attention. Some conventional methods for spectrum sensing are sensitive to uncertain signal and noise, its applicability is limited thereof. In this paper, a novel blind spectrum sensing method is proposed, where low-rank and sparse matrix decomposition is applied to the observation signal of a CR in the frequency domain. Then the ratio of the energy of the sparse part and the received signal in the time domain is considered as the criterion to decide whether the radio frequency band is idle by means of a comparison with a predefined threshold. The proposed method is independent of prior knowledge of signal and white noise, and has a better detection performance. Simulation experiments verify the performance of the proposed method in additive white Gaussian noise(AWGN), Rayleighand Rician channels.展开更多
文摘In this paper, a novel detection criterion is proposed to decide whether primary user(PU) exists based on joint analysis of the variance and correlation for observation signal,considering a correlation within the observed signal. Simultaneously, the corresponding detection thresholds are also designed. Simulation experiments verify the proposed method suits for the observation signal in Additive White Gaussian Noise(AWGN), Rayleigh,Rician channel and the detection performance is improved greatly.
基金supported by the open project fund (No. 201600017) of the National Key Laboratory of Electromagnetic EnvironmentNSFC (No.61471066), China
文摘As a crucial component in Cognitive Radio(CR) networks, spectrum sensing has been attracting lots of attention. Some conventional methods for spectrum sensing are sensitive to uncertain signal and noise, its applicability is limited thereof. In this paper, a novel blind spectrum sensing method is proposed, where low-rank and sparse matrix decomposition is applied to the observation signal of a CR in the frequency domain. Then the ratio of the energy of the sparse part and the received signal in the time domain is considered as the criterion to decide whether the radio frequency band is idle by means of a comparison with a predefined threshold. The proposed method is independent of prior knowledge of signal and white noise, and has a better detection performance. Simulation experiments verify the performance of the proposed method in additive white Gaussian noise(AWGN), Rayleighand Rician channels.
