A amendatory LRP channel condition prediction algorithm base on Kalman Filtering

This paper presents a channel condition prediction method for channel stage changes caused by the mobile move in high speed, which base on Kalman Filtering and Auto Regressive (AR) model. We introduced the selection of the sample and the revision of Kalman after studied traditional solution of LRP algorithms. Next, we extract the data from samples, established the AR model coefficient by a training sequence as the past information, predict the channel condition by the LRP channel prediction, and introduce a decision-making, when channel states have clear changes, revision them by Kalman filter. The algorithm we advanced can avoid the repeating calculation by use LRP algorithm. We found that it obtain the good effect in channel prediction by simulation analysis .