基于信道状态信息的室内感知技术

吴哲夫; 汪晗; 陈骋; 王中友; 黄巍

doi:10.11959/j.issn.1000-0801.2019211

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基于信道状态信息的室内感知技术

研究与开发 | 更新时间：2024-06-05

- 基于信道状态信息的室内感知技术
- Indoor sensing technology based on channel state information
- 电信科学 2019年35卷第10期页码：84-91
- 作者机构：
  
  1. 浙江工业大学信息学院，浙江杭州 310023
  2. 浙江省通信产业服务有限公司，浙江杭州 310000
- 作者简介：
  
  [ "吴哲夫（1971- ），男，浙江工业大学副教授、硕士生导师，主要研究方向为无线通信技术和传感网络应用等" ]
  [ "汪晗（1995- ），男，浙江工业大学硕士生，主要研究方向为无线网络室内环境和人体检测技术" ]
  [ "陈骋（1991- ），男，浙江省通信产业服务有限公司通信工程师，主要研究方向为无线网络应用" ]
  [ "王中友（1973- ），男，浙江省通信产业服务有限公司教授级高级工程师，主要研究方向为计算机网络和物联网技术等" ]
  [ "黄巍（1973- ），男，浙江省通信产业服务有限公司高级工程师，主要研究方向为无线通信技术和计算机应用软件研发等" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;Zhejiang Provincial Natural Science Foundation of China(LY18F010025);浙江省自然科学基金资助项目;Zhejiang Provincial Natural Science Foundation of China(LY13F010011)
- DOI：10.11959/j.issn.1000-0801.2019211
  中图分类号： TN929.5
- 网络出版日期：2019-10，
  
  纸质出版日期：2019-10-20
- 稿件说明：
移动端阅览
吴哲夫, 汪晗, 陈骋, 等. 基于信道状态信息的室内感知技术[J]. 电信科学, 2019,35(10):84-91.

Zhefu WU, Han WANG, Cheng CHEN, et al. Indoor sensing technology based on channel state information[J]. Telecommunications science, 2019, 35(10): 84-91.
吴哲夫, 汪晗, 陈骋, 等. 基于信道状态信息的室内感知技术[J]. 电信科学, 2019,35(10):84-91. DOI： 10.11959/j.issn.1000-0801.2019211.

Zhefu WU, Han WANG, Cheng CHEN, et al. Indoor sensing technology based on channel state information[J]. Telecommunications science, 2019, 35(10): 84-91. DOI： 10.11959/j.issn.1000-0801.2019211.

摘要

广泛存在的 Wi-Fi 网络带来了移动互联网商业服务的巨大发展，也成为现代社会的基础设施之一。从当前 Wi-Fi 网络的核心技术出发，透过无线信道状态分析的角度，阐述了无线感知技术的基本原理和实现方法，论述了近年来无线感知领域的技术创新，特别是基于信道状态信息的室内人体姿态和环境感知技术进展，最后分析了未来的发展趋势，为之后相关的研究提供了参考。

Abstract

The wide spread wireless network has brought about tremendous development of mobile internet business services and has become one of the infrastructures of modern society.The basic principles and implementation methods of wireless sensing technology were expounded from the perspective of wireless channel state analysis.The technological innovation in the field of wireless sensing in recent years was discussed

especially channel state information based human body posture detecting and environmental monitoring.Finally

the future development trend of sensing technology based on wireless communication network was analyzed in order to provide reference for related research.

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references

WANG X Y , GAO L J , MAO S W , et al . CSI-Based fingerprinting for indoor localization:adeep learning approach [J ] . IEEE Transactions on Vehicular Technology , 2017 , 66 ( 1 ): 763 - 776 .

LV J , MAN D , WU Y , et al . Robust WLAN-based indoor intrusion detection using PHY layer information [J ] . IEEE Access , 2018 ( 6 ): 30117 - 30127 .

DOMENICO S D , SANCTIS M D , CIANCA E , et al . Wi-Fi-based through-the-wall presence detection of stationary and moving humans analyzing the doppler spectrum [J ] . IEEE Aerospace ＆ Electronic Systems Magazine , 2018 , 33 ( 5-6 ): 14 - 19 .

KIM Y , MOON T . Human detection and activity classification based on micro-doppler signatures using deep convolutional neural networks [J ] . IEEE Geoscience ＆ Remote Sensing Letters , 2016 , 13 ( 1 ): 8 - 12 .

JIANG H , CAI C , MA X , et al . Smart home based on Wi-Fi sensing:A survey [J ] . IEEE Access , 2018 ( 6 ): 13317 - 13325 .

WEINSTEIN S , EBERT P . Data transmission by frequency-division multiplexing using the discrete fourier transform [J ] . IEEE Transactions on Communications , 1971 , 19 ( 5 ): 628 - 634 .

WONG C Y , CHENG R S , LATAIEF K B , et al . Multiuser OFDM with adaptive subcarrier,bit,and power allocation [J ] . IEEE Journal on Selected Areas in Communications , 1999 , 17 ( 10 ): 1747 - 1758 .

ZHI W , HAN J , WEI X , et al . Efficient and secure key extraction using channel state information [J ] . Journal of Supercomputing , 2014 , 70 ( 3 ): 1537 - 1554 .

HALPERIN D , HU W , SHETH A , et al . Tool release:gathering 802.11n traces with channel state information [J ] . ACM Sigcomm Computer Communication Review , 2011 , 41 ( 1 ): 53 - 53 .

YANG J , ZOU H , JIANG H , et al . CareFi:sedentary behavior monitoring system via commodity WiFi infrastructures [J ] . IEEE Transactions on Vehicular Technology , 2018 , 67 ( 8 ): 7620 - 7629 .

HUANG X , GUO S , WU Y , et al . A fine-grained indoor fingerprinting localization based on magnetic field strength and channel state information [J ] . Pervasive and Mobile Computing , 2017 ( 41 ): 150 - 165 .

LI T , WANG H , SHAO Y , et al . Channel state information–based multi-level fingerprinting for indoor localization with deep learning [J ] . International Journal of Distributed Sensor Networks , 2018 , 14 ( 10 ): 1 - 12 .

HAN S , LI Y , MENG W , et al . Indoor localization with a single Wi-Fi access point based on OFDM-MIMO [J ] . IEEE Systems Journal , 2018 ( 4 ): 964 - 972 .

WU Z F , XU Q , LI J , et al . Passive indoor localization based on CSI and Naive Bayes classification [J ] . IEEE Transactions on Systems,Man,and Cybernetics:Systems , 2018 , 48 ( 9 ): 1566 - 1577 .

WU Z F , LEI J , JIANG Z , et al . Accurate indoor localization based on CSI and visibility graph [J ] . Sensors , 2018 , 18 ( 8 ): 2549 - 2550 .

HSIEH C , CHEN J , NIEN B . Deep learning-based indoor localization using received signal strength and channel state information [J ] . IEEE access , 2019 ( 7 ): 33256 - 33267 .

CHEN H , ZHANG Y , LI W , et al . ConFi:convolutional neural networks based indoor Wi-Fi localization using channel state information [J ] . IEEE Access , 2017 ( 5 ): 18066 - 18074 .

WANG X , MAO S . Deep convolutional neural networks for indoor localization with CSI images [J ] . IEEE Transactions on Network Science and Engineering , 2018 ( 9 ): 2327 - 2339 .

ZHONG S , HUANG Y , RUBY R , et al . Wi-Fire:device-free fire detection using WiFi networks [C ] // IEEE International Conference on Communications,May 21-25,2017,Paris,France . Piscataway IEEE Press , 2017 : 1 - 6 .

徐强 . 基于信道状态信息的室内无源定位技术研究 [D ] . 杭州:浙江工业大学 , 2017 .

XU Q . Research on indoor passive location technology based on channel state information [D ] . Hangzhou:Zhejiang University of Technology , 2017 .

李璐汐 . 基于 WLAN 的人员感知与入侵检测技术研究与设计 [D ] . 北京:北京邮电大学 , 2018 .

LI L X . Research and design of personnel perception and intrusion detection technology based on WLAN [D ] . Beijing:Beijing University of Posts and Telecommunications , 2018 .

周健 . 无线感知网络中基于 CSI 的室内入侵检测与行为识别研究 [D ] . 南京:南京邮电大学 , 2018 .

ZHOU J . Research on indoor intrusion detection and behavior recognition based on CSI in wireless perceptual networks [D ] . Nanjing:Nanjing University of Posts and Telecommunications , 2018 .

LI S , LI X , NIU K , et al . AR-Alarm:an adaptive and robust intrusion detection system leveraging csi from commodity Wi-Fi [C ] // International Conference on Smart Homes and Health Telematics,August 12-16,2017,Cham,Germany . Berlin:Springer , 2017 : 211 - 223 .

TIAN Z , WANG J , YANG X , et al . WiCatch:a Wi-Fi based hand gesture recognition system [J ] . IEEE Access , 2018 ( 6 ): 16911 - 16923 .

MA Y S , ZHOU G , WANG S Q , et al . SignFi:sign language recognition using Wi-Fi [J ] . ACM Interaction Mobile Wearable Ubiquitous Technology , 2018 , 2 ( 1 ): 1 - 21 .

MUHAMMAD S , ZHANG S H . Augmenting user identification with Wi-Fi based gesture recognition [J ] . ACM Interaction Mobile Wearable Ubiquitous Technology , 2018 , 2 ( 3 ): 1 - 27 .

RAGHAV , VENKATNARAYAN , GRIFFIN PAGE . Multi-user gesture recognition using Wi-Fi [C ] // The 16th Annual International Conference on Mobile Systems,CA,USA . New York:ACM Press , 2018 : 401 - 413 .

CHEN J , LI F , CHEN H , et al . Dynamic gesture recognition using wireless signals with less disturbance [J ] . Personal and Ubiquitous Computing , 2019 , 23 ( 1 ): 17 - 27 .

ZHENG X , WANG J , SHANGGUAN L , et al . Smokey:ubiquitous smoking detection with commercial wifi infrastructures [C ] // IEEE International Conference on Computer Communications,April 10-14,2016,San Francisco,USA . Piscataway:IEEE Press , 2016 : 1 - 9 .

LIU J , CHEN Y , WANG Y , et al . Monitoring vital signs and postures during sleep using Wi-Fi signals [J ] . IEEE Internet of Things Journal , 2018 , 5 ( 3 ): 2071 - 2084 .

ZHANG D , HU Y , CHEN Y , et al . Breathtrack:tracking indoor human breath status via commodity Wi-Fi [J ] . IEEE Internet of Things Journal , 2019 ( 99 ): 1 - 1 .

ZENG Y W , YI E , WU D , et al . A full human respiration detection system using commodity Wi-Fi devices [C ] // ACM International Joint Conference,Oct 8-12,2018,Singaproe,Singaproe . New York:ACM Press , 2019 : 480 - 483 .

YANG Y , CAO J , LIU X , et al . Multi-person sleeping respiration monitoring with COTS Wi-Fi devices [C ] // 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS),Oct 9-12,2018,Chengdu,China . Piscataway:IEEE Press , 2018 : 37 - 45 .

LEE S , PARK Y , SUH Y , et al . Design and implementation of monitoring system for breathing and heart rate pattern using Wi-Fi signals [C ] // IEEE Annual Consumer Communications ＆ Networking Conference,Jan 12-15,2018,Las Vegas,NV,USA . Piscataway:IEEE Press , 2018 : 1 - 7 .

WOO S , BYUN J , KIM S , et al . RNN-based personalized activity recognition in multi-person environment using RFID [C ] // IEEE International Conference on Computer and Information Technology.Dec 8-10,2016,Nadi,Fiji . Piscataway:IEEE Press , 2016 : 708 - 715 .

WANG F , GONG W , LIU J . On spatial diversity in Wi-Fi-based human activity recognition:a deep learning based approach [J ] . IEEE Internet of Things Journal , 2019 ( 99 ):1.

CHOWDHURY T Z . Using Wi-Fi channel state information (CSI) for human activity recognition and fall detection [D ] . Vancouver:University of British Columbia , 2018 .

HAO W , ZHANG D , WANG Y , et al . RT-Fall:areal-time and contactless fall detection system with commodity WiFi devices [J ] . IEEE Transactions on Mobile Computing , 2017 , 16 ( 2 ): 511 - 526 .

ZHANG F , ZHANG D , JEI X , et al . From fresnel diffraction model to fine-grained human respiration sensing with commodity Wi-Fi devices [J ] . Proceedings of the ACM on Interactive,Mobile,Wearable and Ubiquitous Technologies , 2018 , 2 ( 1 ): 53 - 76 .

ZHANG Z , ISHIDA S , TAGASHIRA S , et al . Danger-Pose Detection System Using Commodity Wi-Fi for Bathroom Monitoring [J ] . Sensors , 2019 , 19 ( 4 ): 287 - 290 .

DONG Z H , LI F M , YIN J L , et al . Indoor motion detection using wi-fi channel state information in flat floor environments versus in staircase environments [J ] . Sensors , 2018 , 18 ( 7 ): 2177 - 2177 .

WANG Z Q , GU Z H , YIN J W , et al . Syncope detection in toilet environments using Wi-Fi channel state information [C ] // The 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers,Oct 8-12,2018,Singapore . New York:ACM Press , 2019 : 287 - 290 .

YANG Y , CAO J , LIU X , et al . Wi-Count:passing people counting with COTS WiFi devices [C ] // International Conference on Computer Communication and Networks,July 30-Aug 2,2018,Hangzhou,China . Piscataway:IEEE Press , 2018 : 1 - 9 .

LIU S , ZHAO Y , XUE F , et al . DeepCount:crowd counting with Wi-Fi via deep learning [J ] . Signal Processing , 2019 : 211 - 223 .

HUANG H , LIN S . WiDet:Wi-Fi based device-free passive person detection with deep convolutional neural networks [C ] // The 21st ACM International Conference on Modeling,Oct 28-Nov 2,2018,Montreal,Canada,New York:ACM Press , 2018 : 53 - 60 .

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