Investigation and Modeling of Multi-Node Body Channel Wireless Power Transfer †

Insufficient power supply is a huge challenge for wireless body area network (WBAN). Body channel wireless power transfer (BC-WPT) is promising to realize multi-node high-efficiency power transmission for miniaturized WBAN nodes. However, the behavior of BC-WPT, especially in the multi-node scenario, is still lacking in research. In this paper, the inter-degeneration mechanism of a multi-node BC-WPT is investigated based on the intuitive analysis of the existing circuit model. Co-simulation in the Computer Simulation Technology (CST) and Cadence platform and experiments in a general indoor environment verify this mechanism. Three key factors, including the distance between the source and the harvester, frequency of the source, and area of the ground electrodes, are taken into consideration, resulting in 15 representative cases for simulation and experiments studies. Based on the simulation parameters, an empirical circuit model to accurately predict the received power of multiple harvesters is established, which fits well with the measurement results, and can further provide guidelines for designs and research on multi-node BC-WPT systems.

[1]  D. Savitz,et al.  INTERNATIONAL COMMISSION ON NON-IONIZING RADIATION PROTECTION , 2011 .

[2]  Javier Reina-Tosina,et al.  Study of Attenuation and Dispersion Through the Skin in Intrabody Communications Systems , 2012, IEEE Transactions on Information Technology in Biomedicine.

[3]  Jianming Zhang,et al.  Attribute-based knowledge transfer learning for human pose estimation , 2013, Neurocomputing.

[4]  Shreyas Sen,et al.  Wearable health monitoring using capacitive voltage-mode Human Body Communication , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[5]  Huazhong Yang,et al.  Dynamic Channel Modeling and OFDM System Analysis for Capacitive Coupling Body Channel Communication , 2019, IEEE Transactions on Biomedical Circuits and Systems.

[6]  A. Ahlbom Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz) , 1998 .

[7]  国際非電離放射線防護委員会 ICNIRP statement on the "Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz)". , 2009, Health physics.

[8]  Hoi-Jun Yoo,et al.  The Human Body Characteristics as a Signal Transmission Medium for Intrabody Communication , 2007, IEEE Transactions on Microwave Theory and Techniques.

[9]  Rizwan Bashirullah,et al.  Channel characterization for galvanic coupled in vivo biomedical devices , 2011, 2011 IEEE International Symposium of Circuits and Systems (ISCAS).

[10]  Mingui Sun,et al.  A Comparative Study Between Novel Witricity and Traditional Inductive Magnetic Coupling in Wireless Charging , 2011, IEEE Transactions on Magnetics.

[11]  Hoi-Jun Yoo,et al.  The Signal Transmission Mechanism on the Surface of Human Body for Body Channel Communication , 2012, IEEE Transactions on Microwave Theory and Techniques.

[12]  Fei Yu,et al.  A Low-Voltage and Low-Power 3-GHz CMOS LC VCO for S-Band Wireless Applications , 2014, Wireless Personal Communications.

[13]  Yong-Xin Guo,et al.  Investigation and Modeling of Capacitive Human Body Communication , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[14]  Z. Popovic,et al.  Cut the Cord: Low-Power Far-Field Wireless Powering , 2013, IEEE Microwave Magazine.

[15]  Xiaoyan Peng,et al.  Development of a human head and neck muscle activation control model based on BPNN , 2018, J. Intell. Fuzzy Syst..

[16]  Hoi-Jun Yoo,et al.  A 48 μW, 8.88 × 10−3 W/W batteryless energy harvesting BCC identification system , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).

[17]  George Jie Yuan,et al.  Electric-Field Intrabody Communication Channel Modeling With Finite-Element Method , 2011, IEEE Transactions on Biomedical Engineering.

[18]  Bo Zhao,et al.  A Self-Adaptive Capacitive Compensation Technique for Body Channel Communication , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[19]  M. Soljačić,et al.  Wireless Power Transfer via Strongly Coupled Magnetic Resonances , 2007, Science.

[20]  안병철,et al.  Wireless Body Area Networks의 관련기술과 연구경향에 대한 이해 , 2014 .

[21]  Oliver Chiu-sing Choy,et al.  Cascaded Network Body Channel Model for Intrabody Communication , 2016, IEEE Journal of Biomedical and Health Informatics.

[22]  Ieee Standards Board IEEE standard for safety levels with respect to human exposure to radio frequency electromagnetic fields, 3kHz to 300 GHz , 1992 .

[23]  Bo Zhao,et al.  A Five-Tissue-Layer Human Body Communication Circuit Model Tunable to Individual Characteristics , 2018, IEEE Transactions on Biomedical Circuits and Systems.

[24]  Minyi Guo,et al.  HSCS: a hybrid shared cache scheduling scheme for multiprogrammed workloads , 2018, Frontiers of Computer Science.

[25]  JeongGil Ko,et al.  IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications , 2019, Sensors.

[26]  Harinath Garudadri,et al.  Channel Modeling of Miniaturized Battery-Powered Capacitive Human Body Communication Systems , 2017, IEEE Transactions on Biomedical Engineering.

[27]  Javier Reina-Tosina,et al.  Distributed Circuit Modeling of Galvanic and Capacitive Coupling for Intrabody Communication , 2012, IEEE Transactions on Biomedical Engineering.

[28]  Emanuel M. Popovici,et al.  Ultra Low Power Signal Oriented Approach for Wireless Health Monitoring , 2012, Sensors.

[29]  Huazhong Yang,et al.  An Investigation on Inter-degeneration Effect in Body Channel Based Multi-node Wireless Power Transfer , 2018, 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[30]  Guangyao Li,et al.  Multi-Disciplinary Optimization for Multi-Objective Uncertainty Design of Thin Walled Beams , 2010 .