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dc.contributor.authorNaret Suyarojen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.description.abstractThis paper presents an application of the support vector regression (SVR) in prediction of received signal power in the direct sequence code division multiple access (DS/CDMA) systems. The predictor selects the parameters by using five-fold cross-validation method. The results are evaluated in term of minimum mean square error (MMSE.) The inputs for the predictor are the past values of signal series and the output is the next step ahead value. The SVR-based predictor is compared to the previously proposed linear and nonlinear neural network-based predictors, i.e., the adaptive linear (Adaline) predictors and the multilayer perceptrons (MLP), respectively. A noisy Rayleigh fading channel with 1.8 GHz carrier frequency in an urban environment is simulated as the wireless channel. The results show that the SVR-based predictor can estimate the power better than the Adaline and MLP predictors by considering the signal-to-noise ratio (SNR.). ©2008 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titlePower prediction in reverse link for mobile DS/CDMA systems using support vector regressionen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2008en_US
article.volume1en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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