Device-Free Activity Detection and Wireless Localization Based on CNN Using Channel State Information Measurement

Jun Yan, Lingpeng Wan, Wu Wei, Xiaofu Wu, Wei ping Zhu, Daniel Pak Kong Lun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


In this paper, a novel decoupled device-free activity detection and position estimation scheme is proposed using convolutional neural networks and channel state information (CSI) measurement as inputs. For the proposed scheme, the two processes of activity recognition and localization are realized in parallel but independently. Compared with the existing joint approaches, the proposed decoupled scheme is free of error propagation between two processes and achieves better performance especially for position estimation. We also propose a CSI based radio image construction using the amplitude measurement with temporal, spatial and frequency domain information. This has been proven very competitive for feature extraction, compared with the state-of-the-art methods. Extensive experimental and simulation results under a real test setup show the superiority of the proposed scheme.

Original languageEnglish
Pages (from-to)24482-24494
JournalIEEE Sensors Journal
Issue number21
Publication statusPublished - 1 Nov 2021


  • activity recognition
  • channel state information
  • convolutional neural network
  • device-free
  • localization

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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