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用于生物医学植入物的感应链路中的功率与数据传输之间的基本权衡。

Fundamental Trade-Offs Between Power and Data Transfer in Inductive Links for Biomedical Implants.

出版信息

IEEE Trans Biomed Circuits Syst. 2021 Apr;15(2):235-247. doi: 10.1109/TBCAS.2021.3063376. Epub 2021 May 25.

Abstract

This paper studies the fundamental trade-offs between power transfer efficiency (PTE) and spectral efficiency that occur during simultaneous power and data transfer through near-field inductive links. A mathematical analysis is used to establish the relationship between PTE and channel capacity as a function of link parameters such as coupling coefficient ( k), load resistance, and surrounding environment. The analysis predicts that the optimum trade-off between power and data transfer is particularly dependent on k, which is a monotonically-decreasing function of axial distance ( d) between the coils. Real-time adaptation of the link parameters (such as load resistance and modulation type) is proposed to automatically optimize the power-data trade-off over a wide range of distances and coupling coefficients. A bench-top prototype of such an adaptive link is demonstrated at a center frequency of 13.56 MHz. The prototype uses an ultrasound transducer to measure d with accuracy  mm, and uses this information to autonomously optimize both data rate (up to  ∼ 50 Mbps) and PTE (up to  ∼ 25%) as the coil-coil distance varies within the 4-15 mm range.

摘要

本文研究了通过近场感应链路同时进行功率和数据传输时发生的功率传输效率 (PTE) 和频谱效率之间的基本权衡。数学分析用于建立 PTE 与信道容量之间的关系,作为链路参数(例如耦合系数 (k)、负载电阻和周围环境)的函数。分析预测,功率和数据传输之间的最佳权衡特别取决于 k,k 是线圈之间轴向距离 (d) 的单调递减函数。提出了对链路参数(例如负载电阻和调制类型)的实时自适应,以在广泛的距离和耦合系数范围内自动优化功率-数据权衡。在 13.56 MHz 的中心频率下展示了这种自适应链路的台式原型。该原型使用超声波换能器以 0.1mm 的精度测量 d,并使用此信息自动优化数据速率(高达约 50Mbps)和 PTE(高达约 25%),因为线圈-线圈距离在 4-15mm 范围内变化。

相似文献

5
Practical Inductive Link Design for Biomedical Wireless Power Transfer: A Tutorial.实用感应链路设计用于生物医学无线功率传输:教程。
IEEE Trans Biomed Circuits Syst. 2018 Oct;12(5):1112-1130. doi: 10.1109/TBCAS.2018.2846020. Epub 2018 Jul 13.

引用本文的文献

1
Neuromorphic algorithms for brain implants: a review.用于脑植入物的神经形态算法:综述
Front Neurosci. 2025 Apr 11;19:1570104. doi: 10.3389/fnins.2025.1570104. eCollection 2025.
2
Comparative analysis of energy transfer mechanisms for neural implants.神经植入物能量传递机制的比较分析
Front Neurosci. 2024 Jan 16;17:1320441. doi: 10.3389/fnins.2023.1320441. eCollection 2023.

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