Modeling acoustic channel variability in underwater network simulators from real field experimental data

The features of the underwater acoustic channel are remarkably dependent on the considered scenario; for instance, the link quality differs significantly in shallow water with respect to deep water, and series of events such as the presence of rain or ships passing nearby, changes of temperature and wind strength, can change drastically the channel conditions observed in a certain area in different seasons and even during the same day. Mathematical models that consider these parameters exist, but are either very computationally demanding, like the Bellhop ray tracer, or not sufficiently accurate, like the Urick model that often exhibits optimistic results. In this paper, we discuss the development of a statistical channel model based on the analysis of real field experimental data and compare its performance with the other channel models available in the DESERT Underwater network simulator.