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In-body backscatter communication and localization

Published: 07 August 2018 Publication History

Abstract

Backscatter requires zero transmission power, making it a compelling technology for in-body communication and localization. It can significantly reduce the battery requirements (and hence the size) of micro-implants and smart capsules, and enable them to be located on-the-move inside the body. The problem however is that the electrical properties of human tissues are very different from air and vacuum. This creates new challenges for both communication and localization. For example, signals no longer travel along straight lines, which destroys the geometric principles underlying many localization algorithms. Furthermore, the human skin backscatters the signal creating strong interference to the weak in-body backscatter transmission. These challenges make deep-tissue backscatter intrinsically different from backscatter in air or vacuum. This paper introduces ReMix, a new backscatter design that is particularly customized for deep tissue devices. It overcomes interference from the body surface, and localizes the in-body backscatter devices even though the signal travels along crooked paths. We have implemented our design and evaluated it in animal tissues and human phantoms. Our results demonstrate that ReMix delivers efficient communication at an average SNR of 15.2 dB at 1 MHz bandwidth, and has an average localization accuracy of 1.4cm in animal tissues.

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    cover image ACM Conferences
    SIGCOMM '18: Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication
    August 2018
    604 pages
    ISBN:9781450355674
    DOI:10.1145/3230543
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    Published: 07 August 2018

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    • (2024)LiTEfoot: Ultra-low-power Localization using Ambient Cellular SignalsProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699356(535-548)Online publication date: 4-Nov-2024
    • (2024)Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT TagsProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672226(327-339)Online publication date: 4-Aug-2024
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