Modeling the long term fading behaviour in residential wireless sensor networks

Many statistical wireless channel models for different standards and environments have been defined. However, a single stationary statistical model does not reproduce the long term characteristics of the wireless transmission channel sufficiently. When a wireless link is modeled over longer periods of time, changes of the environment must be considered. These changes can be characterized by different phases, which are alternatively experienced by the channel. On top of that, when a whole network is considered, there are interdependencies between the phases experienced by different links. In this paper, a two level hidden Markov wireless residential channel model is described. The global state reflects the presence of residents in the house. It affects all links. The local state of a single link depends on actual movement in the vicinity of that link. Based on the observation of channel measurements a reasonable parameterization is identified. The model can be used to analyze systems for residential control applications with 24/7 operation.