In this article, we have employed an energy detector (ED)-based cooperative spectrum sensing (CSS) with multi-antenna for cognitive radio network (CRN). The spectrum sensing error and energy efficiency (EE) are the key performance parameters in CRN which are affected by the threshold selection method, number of antennas employed at each cognitive user (CU), reporting error probability and cooperative fusion-rule applied at fusion center (FC). Therefore, we have derived the expression for sensing error by considering the effect of all these parameters and have optimized the cooperative fusion-rule at FC by formulating mathematical expression for optimal K in k-out-of-M rule to minimize the sensing error. Since CSS improves the sensing performance of CRN at the cost of increased overhead bits due to more CUs reporting to FC, results reduced EE. We have employed censoring approach to reduce the energy consumption and hence increase the EE of CSS technique. Further, we have illustrated the sensing error and EE improvement achieved under the censoring approach when different threshold selection approaches are employed at each CU. The percentage EE enhancement in censoring approach are 19.53% and 19.9% with constant false-alarm rate (CFAR) and minimized-error probability (MEP) approaches, respectively in comparison to that of the non-censoring approach.

中文翻译：

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基于审查的多天线协作频谱感知方法的优化和认知无线电网络报告信道方案的不完善

在本文中，我们为认知无线电网络（CRN）采用了基于能量检测器（ED）的带有多天线的协作频谱感测（CSS）。频谱感知误差和能效（EE）是CRN中的关键性能参数，受阈值选择方法，每个认知用户（CU）使用的天线数量，报告误差概率以及融合中心采用的合作融合规则的影响（FC）。因此，我们考虑了所有这些参数的影响，得出了感测误差的表达式，并通过公式化了最优的数学表达式，优化了FC上的合作融合规则。M中的k出规则中的K以最小化感测误差。由于CSS由于以更多的CU向FC报告而以增加开销比特为代价提高了CRN的感知性能，因此降低了EE。我们采用了审查方法来减少能耗，从而提高CSS技术的EE。此外，我们已经说明了当在每个CU上使用不同的阈值选择方法时，在审查方法下实现的感测错误和EE改善。与非审查方法相比，采用恒定误报率（CFAR）和最小错误概率（MEP）方法的审查方法的EE增强百分比分别为19.53％和19.9％。