BEAR: A Bursty Error Auto-Regressive Model for Indoor Wireless Environments

In this paper we propose a novel channel model for indoor wireless environments. Using a set of real measurements, we tune the parameters of an Auto-Regressive filter, which is the core of the proposed model; furthermore we assess that its behavior is much closer to real wireless links that those exhibited by some of the most currently used approaches. The novel channel model is integrated within the framework of the Network Simulator environment. Its goal is to mimic the "bursty" behavior that characterizes the aforementioned indoor wireless environments.