A Prediction Algorithm for Real-Time Video Traffic Based on Wavelet Packet

Long-term prediction is a key problem in real-time video traffic applications. Most of real-time video traffic belong to VBR traffic and has specific properties such as time variation, non-linearity and long range dependence. In this paper, feature extraction method of real-time video traffic based on multi-scale wavelet packet decomposition is proposed. On this basis, LMS algorithm is adopted to predict wavelet coefficients. Through reverse wavelet transforms of the predicted wavelet coefficients, the long-term prediction of real-time video traffic is realized. Numerical and simulation results show that this long-term prediction algorithm can accurately track the variation trend of video signal and obtain an excellent prediction result.

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