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A Statistical Signal Processing Approach in Wireless Network Traffic Analysis

Two vital statistics of wireless network namely peak hour call initiated and call drop have been chosen to examine the self similarity and stationarity behaviour of typical wireless network data in this paper. The scaling pattern and nature of fluctuating frequency are exposed through these two parameters. For exposing the scaling nature of the time series that has been taken from the period 3rd March, 2005 to 31st October, 2015, from the local mobile switching server. Statistical methodologies like Rescaled Analysis (R/S) and General Hurst Estimation (GHE) method are being used to detect the scaling nature of the data-series. Both the time series represent the Short Range Dependency (SRD) and anti-persistency behaviour. The stationarity or non-stationarity behaviour of the time series have been examined by Kwiatkowski Phillips Schmidt Shin (KPSS) test and Continuous Wavelet Transform (CWT). Here both the time series shows non stationarity behaviour.