SDR processing delay estimation applying correlation detection for Structure Health Monitoring using Multi-subcarrier Multiple Access

Tatsuki Fujiwara, Yohei Nakano, Jin Mitsugi, Yuusuke Kawakita, Haruhisa Ichikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Wireless and battery-less structural health monitoring (SHM) that detect structural damage at low cost are required. To achieve this, the use of multi-subcarrier multiple access (MSMA) communication method is being considered. In MSMA, time synchronization of sensing data is shifted owing to software defined radio (SDR) processing. Therefore, when an SHM monitoring method requiring time synchronization of sensing data is used, time synchronization taking SDR processing delay into account is necessary. In this study, we propose a system that estimates SDR processing delay by correlation detection and acquires time synchronization of sensing data. We measured SDR delay estimation with time accuracy by installing this system on an experimental object. Results showed that the error of the allowable processing delay estimation was different, and time synchronization can be achieved by performing sensing once by the SDR processing delay estimation method using correlation detection.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on the Internet of Things, IoT 2017
PublisherAssociation for Computing Machinery
VolumePart F132741
ISBN (Electronic)9781450353182
DOIs
Publication statusPublished - 2017 Oct 22
Event7th International Conference on the Internet of Things, IoT 2017 - Linz, Austria
Duration: 2017 Oct 222017 Oct 25

Other

Other7th International Conference on the Internet of Things, IoT 2017
CountryAustria
CityLinz
Period17/10/2217/10/25

Keywords

  • Multi-subcarreier multiple access
  • Multiple access
  • RFID
  • SDR
  • Structural health monitoring

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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