NDLI: Nonlinear prediction of mobile-radio fading channel using recurrent least squares support vector machines and embedding phase space

Content Provider	IEEE Xplore Digital Library
Author	Jiancheng Sun Taiyi Zhang Feng Liu
Copyright Year	2004
Description	Author affiliation: Dept. of Inf. & Commun. Eng., Xi'an Jiaotong Univ., China (Jiancheng Sun; Taiyi Zhang; Feng Liu)
Abstract	Prediction of the rapidly fading mobile-radio channel enables a number of capacity improving techniques, such as fast resource allocation or fast adaptive modulation. We construct an embedding phase space which includes more system information than the scalar time series; then we use a new nonlinear regression method, recurrent least squares support vector machines (RLS-SVM), to resolve the prediction problem. A performance evaluation of the prediction algorithm is carried out with various SNR values on Rayleigh fading channels. The simulation results show that the proposed algorithm is a good method for long range prediction of the fading channel.
Sponsorship	Ministry of Educ. (MOE) of PR China City Univ. of Hong Kong K.C. Wong Educ. Found
Starting Page	282
Ending Page	286
File Size	304953
Page Count	5
File Format	PDF
ISBN	0780386477
DOI	10.1109/ICCCAS.2004.1346063
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fading Support vector machines Delay effects Predictive models Time measurement Iterative algorithms Resource management Sun Least squares methods Land mobile radio
Content Type	Text
Resource Type	Article

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