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In this paper, author consider
cooperative spectrum sensing in order to optimize the sensing
performance and focus on energy detection for spectrum sensing
and find that the optimal fusion rule is the half-voting rule.
Next, the optimal detec
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协作频谱感知虽然可提高系统的感知性能， 但随着感知节点数目的增加， 系统资源的占用越来越多，
系统传输效率下降． 分析了协作频谱感知方法的感知性能， 得到协作频谱感知的感知性能与感知节点数目和接
收信噪比之间的关系， 提出了一种新的次级用户节点的选择方法， 该方法有效保证了所选择节点的感知性能，
仿真验证了该算法的有效性和可靠性．-Although the cooperative spectrum sensing can improve the perceived performan
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仿真实现了关于认知无线电中合作频谱检测的性能分析-Simulation to achieve the performance of cooperative spectrum sensing in cognitive radio
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对基于能量检测的频谱感知的单节点和合作式能量检测做了详细介绍，进行了Matlab仿真，并对仿真进行了性能分析与比较。-Energy detection based spectrum sensing of single node and cooperative energy detection conducted a detailed descr iption and simulation of Matlab simulation performance analysis and comparis
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采用蒙特卡洛仿真，在matlab平台上仿真基于信任的协作频谱感知算法的性能-Monte Carlo simulation, simulation based on matlab platform trusted cooperative spectrum sensing algorithm performance
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matlab仿真设计频谱感知技术，使用and准则仿真实现不同用户合作频谱感知，进行性能仿真。-matlab simulation design spectrum sensing techniques and guidelines for the use of simulation to achieve different user cooperative spectrum sensing, performance simulation。
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In this paper, we analyze the performance of
spectrum sensing based on energy detection. We do not assume
the exact noise variance is known a priori. Instead, an estimated
noise variance is used to calculate the threshold used in the
spectrum
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COOPERATIVE SPECTRUM SENSING performance over rayleigh fading with different applications like different SNR or different number of secondary users or different fusion rules and cooperative relay in cognitive radio and cooperative betweeen primary an
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In this paper we uate the performance of cooperative spectrum sensing (CSS) where
each cognitive radio (CR) employs an improved energy detector (IED) with multiple antennas and
uses selection combining (SC) for detecting the primary user (PU) in
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前已提出的频谱感知方法主要包括匹配滤波器检测、 能量检测、 循环平稳特征检测以及多分辨率频谱感知. 这些方法均为单节点感知方法.然而，在阴影和深度衰落情况下， 单个节点的感知结果并不可靠， 因此， 需要对多个节点的感知结果进行融合，以提高检测可靠性， 即协作感知技术. 文献采用“或” 准则对各个 CR 感知结果进行融合. 文献则提出了基于 D-S 证据理论的协作频谱感知算法，虽然该算法的性能比“或” 准则或“与”准则要好， 但需要存储大量历史信息， 算法的计算复杂度也很高. 文献中分析了采用似然
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