Human body communication (HBC) has several advantages over traditional wireless communications due to the high conductivity of human body. An accurate body channel model plays a vital role in optimizing the performance and power of HBC transceivers. In this paper, we present a body channel model with three distinct features. First, it takes into account all five body tissue layers resulting better accuracy; second, it adapts to different individuals with the proposed layer thickness estimation technique; third, it counts in the variation of backward coupling capacitance versus different postures. These new features significantly improve the model accuracy. Measurement results show that the proposed model achieves a maximum error of 2.21% in path loss for different human subjects.
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| http://dx.doi.org/10.1109/TBCAS.2018.2798410 | DOI Listing |
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