基于卡尔曼滤波的认知无线网络路由算法

Routing Protocol Based on the Kalman Filter for Congnitive Radio Networks

针对认知无线网络中频谱的动态性及节点移动性,提出一种基于卡尔曼滤波的认知无线网络路由算法,以提高链路的稳定性。该算法综合考虑主用户的频谱空闲概率与节点间的距离,兼顾端到端传输时延,对路由尺度进行设计,选择稳定度较高的路径进行通信;在路由维护阶段,通过卡尔曼滤波对节点移动速度进行预测,在链路断裂之前启动路由修复。最后通过NS2进行仿真,结果表明该算法在链路通信的稳定性、分组投递率、吞吐量等方面有明显的改善,提高了网络的整体性能。

A routing algorithm based on the Kalman filter for cognitive radio networks is proposed to solve the problem of dynamic spectrum in cognitive radio networks and node mobility and to improve the stability of the link. Consider the spectrum idle probability of primary users and the distance between nodes,designs routing metrics select a higher stability path to communicate. In the routing maintenance phase, predict the relative distance of the upstream to the downstream node through the Kalman filter and start the routing repair to repair broken link. NS2-based platform CRCN simulation results show that the algorithm in the stability of the communication link, packet delivery ratio, throughput, etc has obvious improvement on the overall performance of the network.