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

fYear

2014

fDate

4-6 Aug. 2014

Firstpage

245

Lastpage

246

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electromagnetics (iWEM), 2014 IEEE International Workshop on

Conference_Location

Sapporo

Type

conf

DOI

10.1109/iWEM.2014.6963727

Filename

6963727