WBAN node data compression energy-saving method

ZHOU Yue-bin; CHEN Jia-shun; MA He-he

doi:10.13873/j.1000-9787(2017)11-0010-04

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WBAN node data compression energy-saving method

更新时间：2025-09-11

- WBAN node data compression energy-saving method
- Vol. 36, Issue 11, Pages: 10-13(2017)
- 作者机构：
  
  1. 湖北文理学院机械与汽车工程学院
  2. 武汉科技大学机械自动化学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2017)11-0010-04
  CLC： TN92
- Published：2017
- 稿件说明：
移动端阅览
[1]周岳斌,陈家顺,马贺贺.无线体域网节点数据压缩节能方法[J].传感器与微系统,2017,36(11):10-13.

ZHOU Yue-bin, CHEN Jia-shun, MA He-he. WBAN node data compression energy-saving method[J]. 2017, 36(11): 10-13.
[1]周岳斌,陈家顺,马贺贺.无线体域网节点数据压缩节能方法[J].传感器与微系统,2017,36(11):10-13. DOI： 10.13873/j.1000-9787(2017)11-0010-04.

ZHOU Yue-bin, CHEN Jia-shun, MA He-he. WBAN node data compression energy-saving method[J]. 2017, 36(11): 10-13. DOI： 10.13873/j.1000-9787(2017)11-0010-04.

摘要

无线体域网（WBAN）节点通常采用电池供电

能量有限且不易频繁更换。为降低节点能耗

提出了一种数据压缩节能方法

采用稀疏表示分类算法识别正常信号

运用压缩感知（CS）理论进行信号压缩采样

将压缩信号发送至基站并进行重构。对WBAN节点采集的心电图信号进行仿真分析

结果表明:心电图信号经压缩后

具有较好的识别与重构性能

在确保数据传输精度前提下

减少了数据采集量和传输量

有效地降低了WBAN节点能耗。

Abstract

Wireless body area network（ WBAN） node is usually powered by batteries

which is energy limited and not easy to change frequently. A data compression energy-saving method is proposed to reduce the energy consumption of WBAN node

adopting sparse representation classification（ SRC） algorithm to identify the normal signal

using compressed sensing（ CS） theory for signal compression sampling

and the compressed signal is sent to the base station for refactoring. The simulation and analysis have been implemented on electrocardiogram（ ECG）signal collected by WBAN nodes

the results show that the ECG signal after compression

has good recognition performance and reconstruction performance

and under the premise that ensure the data transmission precision

reduce the amount of data acquisition and transmission

effectively reduce the energy consumption of WBAN nodes.

关键词

Keywords

references

稀疏随机矩阵有限等距性质分析 [J]. 张波,刘郁林,王开. 电子与信息学报 . 2014(01)

紫外光无线传感器网络节能的研究与仿真 [J]. 柯熙政,陈锦妮. 激光技术 . 2013(02)

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