Weekly WiMAX Traffic Forecasting using Trainable Cascade-Forward Backpropagation Network in Wavelet Domain

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Provided by: International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Topic: Networking
Format: PDF
Worldwide interoperability for Microwave Access (WiMAX) technology is a modern solution for wireless networks. One of the most difficult problems that appears in the WiMAX network is the non uniformity of traffic developed by different base stations. In this paper, the WiMAX traffic forecasting on week basis is done. The traffic time series is decomposed with Stationary Wavelet Transform (SWT). Further these coefficients will be trained and predicted with the trainable cascade-forward backpropagation neural networks. The quality of forecasting obtained is shown in terms of the four parameters.
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