ABSTRACT Due to its robustness to noise uncertainty, Entropy-Based Spectrum Detection (EnBD) has been proposed to sense primary transmissions in cognitive radio networks. Based on the histogram method, the number of bins must be optimal to accurately estimate the entropy of the samples received. In this work, the performance of the EnBD with respect to several rules for determining the number of bins in the histogram is evaluated. And, it is demonstrated that detection performance is different for each of the aforementioned rules due to the probability distribution of the primary signal.

中文翻译：

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用于基于熵的频谱感知的基于直方图的估计技术的数值分析

摘要 由于其对噪声不确定性的鲁棒性，基于熵的频谱检测 (EnBD) 已被提议用于感知认知无线电网络中的主要传输。基于直方图方法，bins的数量必须是最优的，才能准确估计接收到的样本的熵。在这项工作中，评估了 EnBD 在确定直方图中 bin 数量的几个规则方面的性能。并且，证明了由于主信号的概率分布，上述每个规则的检测性能是不同的。