基于表决融合的带宽受限的协作频谱感知算法

协作的频谱感知使认知无线电（CR）网络对主用户进行可靠的检测,并避免了对主用户通信的干扰。数据融合是协作的频谱感知的关键技术。但是当协作认知无线电用户较多时，它们向融合中心汇报的感知信息就会占用大量的带宽。本文提出了将表决融合准则与检查策略相结合的协作频谱感知的方法，来减少发往融合中心的平均感知比特数，从而有效节约传输带宽。推导分析了该算法在理想信道和非理想信道中的频谱感知性能，并给出了这两种情况检测概率的闭合式。仿真结果表明，此种基于表决融合准则的检查协作频谱感知算法的性能最优，即在较高的感知性能下有大量的感知比特的节约。 

Cooperative Spectrum Sensing Algorithm Based on Vote Fusion under Bandwidth Constraints

Cooperative spectrum sensing enables a Cognitive Radio (CR) networks to reliably detect primary users and avoid causing interference to primary user’s communications. The data fusion technique is a key component of cooperative spectrum sensing. However when the number of Cognitive Radio users tends to be very large, the bandwidth for reporting sensing results of the all users to the fusion center will be extremely huge. In this paper, a censoring scheme based on vote fusion rule for cooperative spectrum sensing is proposed to decrease the average number of sensing bits to the fusion center. Consequently, the bandwidth is saved efficiently using this method. The performance of spectrum sensing is investigated for both perfect reporting channels and imperfect reporting channels, and the close formulations of the detection probability are presented. Simulation results show that the performance of the censoring scheme based on vote fusion rule for cooperative spectrum sensing is optimal. It means that the average number of sensing bits decreases greatly with fine sensing performance.