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Deflection coefficient maximization criterion based optimal cooperative spectrum sensing

机译:基于挠度系数最大化准则的最优协作频谱感知

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摘要

This paper proposes an optimal cooperative spectrum sensing scheme, based on the criterion of deflection coefficient maximization of the global decision statistic. Multiple cooperative secondary users serve in the cognitive radio network to provide space diversity for spectrum sensing. After the fusion center acquires the optimal fusion weights, an optimal global threshold setting strategy is utilized to obtain the final global decision. Since the proposed optimal cooperative sensing scheme requires precise estimations of primary user signal strengths and the noise variances at different cooperative secondary users, a recursive estimate algorithm is also proposed. Simulations illustrate the proposed optimal soft fusion scheme can significantly improve the spectrum sensing performance and outperform the conventional maximal-ratio combining and equal gain combining schemes. The recursive estimate algorithm can effectively approach the ideal performance of the proposed sensing scheme.
机译:基于全局决策统计量的偏转系数最大化准则,提出了一种最优的协作频谱感知方案。多个协作辅助用户在认知无线电网络中提供服务,以提供频谱感知的空间分集。融合中心获取最优融合权重后,采用最优全局阈值设置策略来获取最终的全局决策。由于提出的最优合作感知方案需要精确估计主要用户信号强度和不同合作辅助用户处的噪声方差,因此还提出了一种递归估计算法。仿真结果表明,所提出的最优软融合方案可以显着提高频谱感知性能,并优于传统的最大比合并和等增益合并方案。递归估计算法可以有效地接近所提出的感知方案的理想性能。

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