Title :
Performance analysis of AR-model-based linear predictor with Kalman filtering algorithm for wireless communication systems
Author :
Yamada, Wataru ; Sasaski, Motoharu ; Sugiyama, Takatoshi ; Holland, Oliver ; Aghvami, Hamid
Author_Institution :
NTT Access Network Services Syst. Labs., NTT Corp., Yokosuka, Japan
Abstract :
This paper reports the performance analysis of a proposed auto-regressive (AR) model-based linear predictor algorithm with Kalman filtering (KF). The relationship between the optimum AR order and the channel correlation coefficient is investigated by means of the Akaike Information Criterion (AIC). Through our analysis, 2nd-order differential model based on the AR model-based linear predictor algorithm with KF has the best performance and prediction accuracy. Its performance is about 0.5dB better than a linear predictor algorithm.
Keywords :
Kalman filters; autoregressive processes; prediction theory; wireless channels; Akaike information criterion; Kalman filtering algorithm; auto-regressive model-based linear predictor algorithm; channel correlation coefficient; optimum AR order; performance analysis; wireless communication systems; Accuracy; Algorithm design and analysis; Correlation coefficient; Kalman filters; Mathematical model; Prediction algorithms; Predictive models; AR model; Channel correlation coefficient; Channel prediction algorithms; Kalman filtering;
Conference_Titel :
Electromagnetics (iWEM), 2014 IEEE International Workshop on
Conference_Location :
Sapporo
DOI :
10.1109/iWEM.2014.6963727
