In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...

In the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous...

In this paper, a characterization of the 868 MHz off-body radio channel in BANs is presented. Measurements were carried out in a ferry environment using a specific set-up. A method for path loss using radio distance measurements (RDMs) was developed. It allows to automate the measurements process and make it independent from the variable speed of a moving person. Based on the observed path loss as a function of distance, the obtained...