机构地区: 中山大学信息科学与技术学院
出 处: 《桂林工学院学报》 2008年第2期270-272,共3页
摘 要: 提出了一种基于卡尔曼滤波和AR模型的、针对由于移动台高速移动而引起的信道状态变化的信道预测方法。在研究传统的LRP信道预测算法的基础上抽取采样数据,通过训练序列得到AR模型系数,采用LRP信道预测算法进行信道预测,并引入一个决策模块,当信道状态变化较大时,采用Kalman滤波进行替代预测,可获得较好的预测性能。 A channel condition prediction method based on Kalman Filtering and Auto Regressive(AR) model for channel stage change by the mobile movement at high speed is established.From the selection of the sample and the revision of Kalman after traditional solution study of LRP,algorithms are obtained.From the samples data and the AR model coefficient by a training sequence the channel condition is predicted in LRP channel prediction.A decision-making is introduced.When channel states change,Kalman filter is used.The algorithm calculation is obtained with good effect in channel prediction by simulation analysis.