This paper proposes a new scheme for blind distributed spectrum sensing (DSS), where multiple distributed cognitive radios (CRs) and a fusion center (FC) collaboratively detect the availability of a frequency band of interest under communications constraints without knowledge on the channels, signal power, or noise power. By following the energy detection and homogeneity test concepts, in the proposed scheme, the CRs make local binary decisions based on relative comparison of the total energy in a sampling window, particularly, whether a CR has the maximum total energy. With independent channels, the use of the maximum function generates desirable discrepancy among the CR decisions when the frequency band is in use. The introduction of the window size enables the balancing between communications costs and the performance. Closed-form results on the distribution of the CR decisions are obtained for Gaussian noises and signals. Further, asymptotic analytical expressions are derived on the detection performance of the proposed scheme for both the generalized likelihood ratio test (GLRT) and χ2\chi ^{2} -test at the FC. Simulation results are shown which validate the theoretical results and show the advantage of the proposed scheme to others.

中文翻译：

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一种具有均匀性测试的盲分布式频谱感知方案


本文提出了一种盲分布式频谱感知（DSS）新方案，其中多个分布式认知无线电（CR）和融合中心（FC）在通信约束下协作检测感兴趣频段的可用性，而无需了解信道、信号功率，或噪声功率。通过遵循能量检测和均匀性测试的概念，在所提出的方案中，CR基于采样窗口中总能量的相对比较，特别是CR是否具有最大总能量来做出局部二元决策。对于独立信道，当频段在使用时，最大函数的使用会在 CR 决策之间产生理想的差异。窗口大小的引入实现了通信成本和性能之间的平衡。针对高斯噪声和信号获得了 CR 决策分布的闭合形式结果。此外，针对广义似然比检验（GLRT）和 FC 处的 χ2\chi ^{2} 检验，推导了所提出方案的检测性能的渐近解析表达式。仿真结果验证了理论结果并向其他人展示了所提出方案的优势。