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Proceedings Paper

Estimation and prediction of noise power based on variational Bayesian and adaptive ARMA time series
Author(s): Jingyi Zhang; Yonggui Li; Yonggang Zhu; Binwu Li
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Paper Abstract

Estimation and prediction of noise power are very important for communication anti-jamming and efficient allocation of spectrum resources in adaptive wireless communication and cognitive radio. In order to estimate and predict the time-varying noise power caused by natural factors and jamming in the high frequency channel, Variational Bayesian algorithm and adaptive ARMA time series are proposed. Through establishing the time-varying noise power model, which controlled by the noise variance rate, the noise power can be estimated with Variational Bayesian algorithm, and the results show that the estimation error is related to observation interval. What’s more, through the analysis of the correlation characteristics of the estimation power, noise power can be predicted based on adaptive ARMA time series, and the results show that it will be available to predict the noise power in next 5 intervals with the proportional error less than 0.2.

Paper Details

Date Published: 16 April 2014
PDF: 7 pages
Proc. SPIE 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014), 91590O (16 April 2014); doi: 10.1117/12.2064180
Show Author Affiliations
Jingyi Zhang, PLA Univ. of Science and Technology (China)
Yonggui Li, Nanjing Telecommunication Technology Institute (China)
Yonggang Zhu, Nanjing Telecommunication Technology Institute (China)
Binwu Li, PLA Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9159:
Sixth International Conference on Digital Image Processing (ICDIP 2014)
Charles M. Falco; Chin-Chen Chang; Xudong Jiang, Editor(s)

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