Computer Science ›› 2020, Vol. 47 ›› Issue (11): 327-332.doi: 10.11896/jsjkx.190900019

• Computer Network • Previous Articles    

NWI:CSI Based Non-line-of-sight Signal Recognition Method

TIAN Chun-yuan, YU Jiang, CHANG Jun, WANG Yan-shun   

  1. Department of Information,Yunnan University,Kunming 650500,China
  • Received:2019-09-01 Revised:2019-11-19 Online:2020-11-15 Published:2020-11-05
  • About author:TIAN Chun-yuan,born in 1995,Ph.D.Her main research interests include advanced wireless communication and Internet of things.
    YU Jiang,born in 1961,professor.His main research interests include network communication theory,wireless communication systems,radio monitoring and positioning,and image processing.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61162406),Open Project of Key Laboratory of Spectrum Sensing and Frontier Radio Security of Colleges and Universities in Yunnan Province (C6165903) and Graduate Research Innovation Project of YunnanUniversity(Y2000211).

Abstract: Due to the influence of complex and changeable indoor environment and multipath effects on WiFi signal propagation,a large number of non-line-of-sight paths are generated,which lead to serious signal fading and communication link quality dete-rioration,resulting in low recognition accuracy and complex system implementation.In this paper,a CSI-based NWI (NLOS recognition based on Wavelet Packet Transform Identification) is proposed,which is mainly used for feature extraction of CSI signals,the physical layer information of WiFi,to identify whether there is blocking in the current link.The three-layer wavelet packet is used to decompose the amplitude of CSI signal,the wavelet packet coefficients,wavelet packet energy spectrum,information entropy and logarithmic energy entropy of 8 frequency bands in the third layer are extracted as feature vectors,and the support vector machine is used for classification.Thereby a non-line-of-sight signal is identified.Compared with other methods,the proposed method does not need to pre-process the CSI signal,and the influence of the environment on transmission signals is maximum retained,so as to reflect the indoor environment more realistically.The experimental results show that the recognition accuracy of the proposed method is 96.23% in the dynamic environment and 94.75% in the static environment.It is proved that the CSI signal feature extraction method based on wavelet packet transform can effectively identify non-line-of-sight signals and has high recognition accuracy and universality.

Key words: Channel state information, Feature extraction, Non-line-of-sight signal recognition, Support vector machine, Wavelet packet transform

CLC Number: 

  • TN99
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