基于节点识别的协作频谱检测算法

在认知无线网络协作频谱感知过程中,感知节点所处的恶劣信道环境会导致本地频谱检测结果发生偏差,有时一些故障节点或恶意节点发送的误导信息来干扰认证网络融合中心的全局判决.根据认知网络感知节点的历史感知信息,将感知节点分为可信节点、不可信节点和故障或恶意节点,提出了一种基于节点识别的协作频谱检测算法.在该算法中,融合中心舍弃故障或恶意节点,使其不得参与数据融合,同时也不考虑不可信节点当前发送的本地检测结果.这样,一方面消除了故障或恶意节点对全局频谱判决的影响,另一方面降低了融合中心计算复杂度.仿真结果表明,该算法能有效克服故障或恶意节点的干扰,提高认证网络协作频谱检测性能.

Cooperative Spectrum Detection Algorithm Based on Node Recognition

The poor channel environment of cognitive radio networks often results in the decline of local spectrum detection performance during cooperative spectrum sensing. Sometimes, fault nodes or malicious nodes deliberately send some wrong information to disturb the fusion center to make global decision. According to the historical sensing information of sensing nodes, the sensing nodes are classified intoreliable nodes, fault or malicious nodes and unreliable nodes, and a cooperative spectrum detection algorithm is proposed based on node recognition. Therefore, the fault or malicious nodes are discarded and prevented from data fusion in fusion center. At the same time, the current local detection results of unreliable nodes are not considered in current global decision. Thus, not only the effect of fault or malicious nodes on the global decision is eliminated, but also the calculation complexity of fusion center is reduced. The simulation results show that the proposed algorithm can avoid the interference of fault or malicious nodes and improve spectrum sensing performance effectively.