无线传感器网络中基于贝叶斯准则融合的协作频谱感知算法

文中将认知无线电应用于无线传感器网络中,考虑了传感器节点的能量有限、传输数据量较多、频谱资源受限、次用户如何避免占用主用户信道等情况下,构建一种认知无线传感器系统模型.该系统在对授权用户不造成干扰的前提下提高频谱利用率,解决频谱资源受限的问题,并在此基础上提出了基于贝叶斯准则融合的协作频谱感知方案,同时定量的分析了虚警代价与漏验代价对系统的影响.仿真结果表明,相比传统的或融合、与融合协作频谱感知方案而言,该方案较好的提高了无线传感器网络频谱感知的可靠性和准确性,同时更明确地指出虚警代价相比于漏验代价大时,可有效地使系统平均总代价降低.

Cooperative Spectrum Sening Algorithm Based on Bayesian Rule Fusion in Wireless Sensor Network

This article introduces Cognitive Radio into WSN,considering the energy limited sensor node,large quantities of data,limited spectrum resources,and secondary users how to avoid occupying the main channel,to build a Cognitive Wireless Sensor system model.The spectrum utilization has been improved with the authorized users not being interfered.The cooperative spectrum sensing scheme based on Bayesian rule fusion has been proposed in this system.The impact on the system with the cost of false alarm and leak test are analyzed.The simulation results show that,compared with the traditional or fusion and fusioncollaborative spectrum sensing scheme,Bayesian rule fusion has improved the reliability and accuracy of spectrum perception in Wireless Sensor Network greatly.It is also show that when the cost of false alarm is larger than the cost of leak test,the average total cost is reduced effectively.