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Cooperative spectrum sensing (CSS) is an approach to confront fading environment. However, in conventional cooperative spectrum sensing (CCSS), the difference among the secondary users (SUs) is ignored when SUs suffer from different fading. In this article, a signal-to-noise ratio (SNR)-based weighted spectrum sensing scheme is proposed to improve the sensing performance. The sensing performance of the weighted spectrum sensing scheme is then derived. Considering the minor contribution of the SUs with small weighted factor, a selective CSS scheme is proposed, where SUs with low SNR are not selected into cooperative spectrum sensing. The simulation results confirm the analytical results. And the performance of weighted scheme is better than that of conventional schemes. In the case where the SNR of SUs are randomly distributed, the performance of selective scheme is almost the same as the weighted scheme while the number of cooperative SUs is reduced to save the consumption of system resource in cooperation with little additional complexity.
Cooperative spectrum sensing (CSS) is an approach to confront fading environment. However, in conventional cooperative spectrum sensing (CCSS), the difference among the secondary users (SUs) is ignored when SUs suffer from different fading. In this article, a signal- to-noise ratio (SNR) -based weighted spectrum sensing scheme is proposed to improve the sensing performance. The sensing performance of the weighted spectrum sensing scheme is then derived. Considering the minor contribution of the SUs with small weighted factor, a selective CSS scheme is the proposed, where SUs with low SNR are not selected into cooperative spectrum sensing. And the performance of weighted schemes is better than that of conventional schemes. In the case where the SNR of SUs are randomly distributed, the performance of selective scheme is almost the same as the weighted scheme while the number of cooperative SUs is reduced to save the consumption of system re source in cooperation with little additional complexity.