Browsing by Author "Tanghe, Emmeric"

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    Characterization of dynamic wireless body area network channels during walking
    (Springer International Publishing, 2019-04-29) Mohamed, Marshed; Joseph, Wout; Vermeeren, Günter; Tanghe, Emmeric; Cheffena, Michael
    In this work, finite-difference time-domain was used for the investigation of dynamic wireless body area network channel characteristics during walking, thus accounting for dynamic aspects and body postures. This involves the study of on-body, off-body, and body-to-body communication in an empty environment, at the center frequency of 2.45 GHz. The channels were investigated in terms of fade variation and their corresponding amplitude distributions. For on-body channels, the fade variation was found to be periodic, with larger fade variations for the channels involving the nodes at the hand and thigh. For off-body and body-to-body channels, channels with the absence of line of sight experienced constructive and destructive interference as the distance between the end nodes changes, resulting in larger fade variations. For the amplitude distribution of the channels, a multivariate normal distribution was considered. The distribution has the capability of modeling channels jointly which makes it easier for network analysis and was considered because of the significant correlation between the channels. The resulting estimated multivariate distributions fit well with the simulated data, for on-body, off-body, and body-to-body channels
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    Characterization of Off-Body Area Network Channels During Walking
    (IEEE, 2019-05-08) Mohamed, Marshed; Joseph, Wout; Heat, Günter; Tanghe, Emmeric; Cheffena, Emmeric
    In this work, the off-body area network channel characteristics during walking were investigated using finite-difference time-domain. The channels were investigated in terms of fade variation and the correlation between different channels. Larger fade variations were experienced by the channel with the absence of line-of-sight, due to constructive and destructive interference as the distance between the end nodes changes. The channels showed significant correlation and hence a multivariate normal distribution was considered. The distribution has the capability of modeling channels jointly which make it easier for network analysis. The resulting estimated multivariate distributions fit well with the simulated data.