Channel Modeling of Miniaturized Battery-Powered Capacitive Human Body Communication Systems

January 28, 2017

feb2tbme001122016largeJiwoong Park, Harinath Garudadri, and Patrick P. Mercier, University of California San Diego, USA

The purpose of this contribution is to estimate the path loss of capacitive human body communication (HBC) systems under practical conditions. Most prior work utilized large, grounded instruments to perform path loss measurements, resulting in overly optimistic path loss estimates that may not be realizable for wearable HBC devices. In this paper, small battery-powered transmitter and receiver devices are implemented to measure path loss under realistic assumptions. Also, a hybrid electrostatic-FEM simulation model is presented that validates measurements and enables rapid and accurate characterization of future capacitive HBC systems. Form-factor-accurate wearable prototypes measured over a 20 cm distance on a human forearm, reveal path loss results between 31.7 and 42.2 dB from 20 to 150 MHz. Simulation results matched measurements within 2.5 dB. Co-measurements using large grounded benchtop vector network analyzer (VNA) and large battery-powered spectrum analyzer (SA) underestimate path loss by up to 33.6 and 8.2 dB, respectively. Measurements utilizing a VNA with baluns, or large battery-powered SAs with baluns still underestimate path loss by up to 24.3 and 6.7 dB, respectively. Since measurements of path loss in capacitive HBC systems were shown to strongly depend on instrumentation configurations, it is thus imperative to simulate or measure path loss in capacitive HBC systems utilizing realistic geometries and grounding configurations. HBC has a great potential for many emerging wearable devices and applications; accurate path loss estimation will improve system-level design leading to viable products.

Keywords: body area networks, body-sensor networks, capacitive coupling, channel modeling, human body communication, short-range radios, ultra-low-power communication, wearable devices

Website: http://efficiency.ucsd.edu

 

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