基于可信度的加权协作频谱检测算法

Reliability-Based Weighted Cooperative Spectrum Sensing Algorithm

协作频谱检测技术可以有效解决认知无线网络本地检测存在的信道衰落、隐藏终端等问题.本文研究了加权协作频谱检测技术,提出一种基于可信度的协作频谱检测算法.每个感知节点基于最大最小值特征值检测完成本地频谱检测,并与融合中心的全局检测结果进行比较,估计各自感知节点的频谱检测可信度;融合中心利用切尾平均法计算参与频谱协作检测的可信度门限,并选择可信度大于门限的感知节点参与协作频谱检测.该算法有效降低了认知网络协作检测的复杂性,提高了频谱检测性能,在噪声波动环境下具有良好的鲁棒性.仿真结果表明,算法频谱检测性能要优于其他加权算法1～3 dB,节省系统开销43.75％左右.

Cooperative spectrum sensing can solve the problems such as channel fading or hidden terminal in local spectrum sensing of cognitive radio network effectively. This paper considers the weighted cooperative spectrum sensing technology and proposed a reliability-based cooperative spectrum sensing algorithm. In the algorithm, the local spectrum decision is obtained with the maximum-eigenvalue-based detection scheme in each sensing user. Then it is compared with the global decision and the reliability of each sensing user is estimated in fusion center. The fusion center reckons the credibility threshold using of the trimmed mean and selects the users which reliabilities are larger than the credibility threshold to participate in the cooperative spectrum sensing. This algorithm reduces the complexity of the system, improves the performance of the spectrum sensing, and is robust to the noise uncertainty. Simulation results show that the proposed algorithm outperforms other weighted algorithms 1-3 dB in signal to noise ratio and save the communication overhead 43.75% or so.