Channel modeling and power consumption analysis for galvanic coupling intra-body communication

Intra-body communication (IBC), using the human body as the channel to transmit data, has lower power consumption, less radiation, and easier linking than common wireless communication technologies such as Bluetooth, ZigBee, and ANT. As a result, IBC is greatly suitable for body area network (BAN) applications, such as the medical and health care field. Furthermore, IBC can be implemented in wearable devices, including smart watches, sports bracelets, somatic game devices, and multimedia devices. However, due to the limited battery capacity of sensor nodes in a BAN, especially implanted sensor nodes, it is not convenient to charge or change the batteries. Thus, the energy effectiveness of the media access control (MAC) layer strongly affects the life span of the nodes and of the entire system. Certainly, analyzing MAC layer performance in a galvanic coupling IBC is of great importance for the overall system. To obtain the attenuation properties of IBC, in vivo experiments with seven volunteers were performed. Meanwhile, an equalizer was used to compensate the frequency distortion in consideration of frequency-selective fading characteristics of intra-body channels. In addition, a comparison of the bit error rates (BER) of different modulation methods was carried out to obtain the best modulation method. Then, the attenuation characteristics of intra-body channels were applied in a multi-node physiological signal monitor and transmission system. Finally, TDMA and CSMA/CA protocols were introduced to calculate the bit energy consumption of IBC in the practical scenario. With stable characteristics of the intra-body channels, QPSK with an equalizer had a better performance than the tests without an equalizer. As a result, the modulation method of FSK could achieve a lower BER in lower signal-to-noise ratio situations and an FSK method with TDMA for the IBC had the lowest energy consumption under different practical scenarios.