基于鱼群算法的无线传感网簇内信号盲检测

Blind Detection for Signals within Cluster of Wireless Sensor Networks Based on Artificial Fish School Algorithm

文中在无线传感网传输模型分簇的基础上,针对簇内信号盲检测降低误码率和提高收敛性问题,提出了一种基于人工鱼群算法的信号盲检测算法。该算法采用自下而上的设计,构造了人工鱼的基本模型以及其各行为的模型,不需要了解问题的特殊信息,只需要对问题解的优劣进行比较,用此模型解决无线传感网簇内盲信号检测的二次规划性能函数。仿真结果表明,算法具有全局收敛性好、收敛速度快、误码率低的优点,从而成功实现了簇内簇首传感器信号盲检测。

Based on model clustering in wireless sensor network transmission in this paper,in viewof the problem of cluster signal blind detection lowering bit error rate and improving convergence,a signal blind algorithm based on artificial fish school algorithm is proposed.The bottom- up design is used in the novel algorithm and the basic model of artificial fish and its various models of behavior are constructed. It doesn＇t need to knowthe problem ＇s special information and only to compare the advantage and disadvantage for the problem solution. The quadratic programming performance functions of inter- cluster signals is solved by the algorithm. Simulation results showthat the algorithm has the advantages of good global convergence,quick convergence speed,lowerror rate,thus successfully implementing blind detection of sensor signal within the cluster and in the cluster head.