认知无线电中频谱感知方法的性能与感知场景高度相关. 研究表明, Nakagami-Gamma(KG)衰落信道模型能够可靠地描述无线通信信道. 针对采样点数、接收信噪比、地理位置等多种性能影响因素各不相同的一组异构节点在KG衰落信道下的感知场景, 提出了一种基于熵函数(based on entropy function, BEF)的合作感知方法. 首先, 根据异构节点的不同性能影响因素, 通过定义的熵函数计算各节点的综合评价得分; 然后, 筛选出得分较高的节点进行标准化能量检测; 最后, 采用逻辑或(OR)准则进行融合判决. 仿真结果表明, BEF方法有效地降低了系统的感知开销, 在各个节点的目标虚警概率较低($P_{\rm f}<0.1$)时, 显著提升了全局检测概率.

In cognitive radio, the performance of the spectrum sensing method is closely related to the sensing scene. Research has shown that the Nakagami-Gamma (KG) fading channel model can reliably describe wireless communication channels. A cooperative sensing method based on the entropy function (BEF) is proposed for the sensing scene of heterogeneous nodes (a group of nodes with different performance factors such as sampling number, receiving signal-to-noise ratio (SNR), and geographical location) in the KG fading channel. First, the comprehensive evaluation scores of each node are calculated using the defined entropy function according to the different performance factors of heterogeneous nodes. Then, the nodes with high scores are selected for normalised energy detection. Finally, the OR criterion is used for fusion decision. Simulation results show that the proposed BEF method can effectively reduce the overhead of the sensing system, and the global detection probability is significantly improved when the target false alarm probability of each node is low ($P_{\rm f}<0.1$).