• DocumentCode
    2281802
  • Title

    Investigation on Signal Modulation Recognition in the Low SNR

  • Author

    Liu Ning ; Liu Bing ; Guo Shuxia ; Luo Ronghui

  • Author_Institution
    Nat. Key Lab. of UAV Specialty Tech., Northwestern Polytech. Univ., Xi´an, China
  • Volume
    2
  • fYear
    2010
  • fDate
    13-14 March 2010
  • Firstpage
    528
  • Lastpage
    531
  • Abstract
    Because of a low Signal-to-noise ratio (SNR), generally the recognition rate and recognition efficiency of signal modulation type are low, but the algorithm is complex. The recognition method of wide-band signal modulation type in the low SNR is studied. Based on the analyzing the characteristic of signal in time domain, frequency domain and power spectrum, three characteristic with fine classification feature are selected, and single k-NN Nearest-neighbor pattern classifier is adopted, and high recognition-rate of several wide-band signal modulation types is achieved in low SNR. The computer simulation results show that this method possesses perfect ability of modulation recognition to signals in a SNR of above 3dB, with an average recognition-rate higher than 99%. In addition, the design of recognition system is simple. It will have significant application value in detecting wireless signals.
  • Keywords
    broadband networks; image recognition; pattern classification; SNR; classification feature; frequency domain; k-NN nearest-neighbor pattern classifier; power spectrum; signal modulation recognition investigation; signal-to-noise ratio; time domain; wide-band signal modulation; Application software; Character recognition; Computer simulation; Frequency domain analysis; Pattern analysis; Pattern recognition; Signal analysis; Signal to noise ratio; Time domain analysis; Wideband; Nearest-neighbor pattern; low SNR; modulation recognition; wide-band signal;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
  • Conference_Location
    Changsha City
  • Print_ISBN
    978-1-4244-5001-5
  • Electronic_ISBN
    978-1-4244-5739-7
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2010.444
  • Filename
    5458822