DocumentCode :
3354376
Title :
Channel Prediction with Cascade AR Modeling
Author :
Lee, Yunho
Author_Institution :
Purdue University
fYear :
2006
fDate :
19-25 Feb. 2006
Firstpage :
40
Lastpage :
40
Abstract :
Cascade autoregressive (AR) model with three parameters for any channel prediction order p is investigated. Although higher order AR model is better to get more precise future channel prediction profile, as the order of channel prediction goes higher, the number of channel prediction parameters we have to know is increased. Besides that, the pole locations may be extremely sensitive function of the coefficients for high order filter. If we use the cascade form of lower order filters which is already used as one of fading generation methods, we can get more stable AR model for higher order channel prediction. Moreover, due to a Doppler spectrum characteristic which has only two peaks at the positive and negative maximum Doppler frequency, we just have to know the second and the first order filter to make cascade AR model of higher order, that is, we can make higher AR model to predict future channel with only three parameters.
Keywords :
Digital filters; Fading; Frequency; IIR filters; Kalman filters; Power system modeling; Power system reliability; Predictive models; Time varying systems; Transmitters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Telecommunications, 2006. AICT-ICIW '06. International Conference on Internet and Web Applications and Services/Advanced International Conference on
Print_ISBN :
0-7695-2522-9
Type :
conf
DOI :
10.1109/AICT-ICIW.2006.62
Filename :
1602172
Link To Document :
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