Comparison of wavelet families with application to WiMAX traffic forecasting

This paper deals with a wavelet based forecasting method for WiMAX traffic time series. It is based on an algorithm composed by a few steps. One of these steps is the computation of the Stationary Wavelet Transform, SWT. This transform has two parameters: the mother wavelet which generates the decomposition and the number of decomposition levels. The aim of this paper is to propose a strategy for the selection of the first parameter. Our work is centered on the following wavelet families Daubechies, Coiflet, Symmlet, Biorthogonal and Reverse Biorthogonal. Some simulation results prove the efficiency of the proposed selection method.