Channel modeling and reliability assessment for Body-centric wireless communications

Wireless Body Area Networks (WBANs) are one of the emerging technological trends that have gained a lot of attention both from academic and industrial domains. WBAN, as standardized by IEEE 802.15.6, is a network composed of intelligent, miniaturized, low power nodes that are implanted in, placed on or in close proximity of human body for certain healthcare applications. Sensors send their acquired data to a central hub wirelessly for further processing. In this paper, based on a publicly available channel data set, we investigate the applicable channel models in a typical WBAN. Considering various scenarios with different carrier frequencies, bandwidths, body movements, and transceiver locations, the well-known Bayesian Information Criterion (BIC) is used to quantify how well a specific model fits the empirical data. At the next step, the reliability concept is introduced as an unavoidable requirement in the majority of medical use cases. The data is now evaluated to derive the reliability of different WBAN sensors. It is shown that the outcomes of such an analysis may give the network designer crucial insights about the positioning of the sensors as well as the central hub.