LiTGen is an easy to use and tune open-loop traffic generator that statistically models wireless traffic on a per user and application basis. We first show how to calibrate the underlying hierarchical model, from packet level capture originating in an ISP wireless network. Using wavelet and semi-experiments analysis, we then prove LiTGen’s ability to reproduce accurately the captured traffic burstiness and internal properties over a wide range of timescales. In addition the flexibility of LiTGen enables us to investigate the sensitivity of the traffic structure with respect to the possible distributions of the random variables involved in the model. Finally this study helps understanding the traffic scaling behaviors and their corresponding internal structure.