Dynamic Channel Modeling for Multi-Sensor Body Area Networks

A channel model for time-variant multi-link wireless body area networks (WBANs) is proposed in this paper, based on an extensive measurement campaign using a multi-port channel sounder. A total of 12 nodes were placed on the body to measure the multi-link channel within the created WBAN. The resulting empirical model takes into account the received power, the link fading statistics, and the link auto- and cross-correlations. The distance dependence of the received power is investigated, and the link fading is modeled by a log-normal distribution. The link autocorrelation function is divided into a decaying component and a sinusoidal component to account for the periodical movement of the limbs caused by walking. The cross-correlation between different links is also shown to be high for a number of specific on-body links. Finally, the model is validated by considering several extraction-independent validation metrics: multi-hop link capacity, level crossing rate (LCR) and average fade duration (AFD). The capacity aims at validating the path-loss and fading model, while the LCR and AFD aim at validating the temporal behavior. For all validation metrics, the model is shown to satisfactorily reproduce the measurements, whereas its limits are pointed out.