• DocumentCode
    1971468
  • Title

    Compressive sampling based multiple symbol differential detection for UWB IR signals

  • Author

    Gishkori, Shahzad ; Leus, Geert ; Lottici, Vincenzo

  • Author_Institution
    Fac. of EEMCS, Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2012
  • fDate
    17-20 Sept. 2012
  • Firstpage
    130
  • Lastpage
    134
  • Abstract
    In this paper, a compressive sampling (CS) based multiple symbol differential detector is proposed, using the principle of a generalized likelihood ratio test (GLRT). The proposed detector works on the compressed samples directly, thereby avoiding the reconstruction step and thus resulting in a reduced implementation complexity along with a reduced sampling rate (much below the Nyquist rate). We also propose the compressed sphere decoder (CSD) to resolve the detection of multiple symbols. Our proposed detector is valid for scenarios where the measurement matrices are the same as well as where they are different for each received symbol.
  • Keywords
    matrix algebra; signal detection; signal reconstruction; signal sampling; ultra wideband technology; CS based multiple symbol differential detector; CSD; GLRT; Nyquist rate; UWB IR signals; compressed samples; compressed sphere decoder; compressive sampling; generalized likelihood ratio test; implementation complexity; measurement matrices; multiple symbol detection; multiple symbol differential detection; reconstruction step; reduced sampling rate; Bit error rate; Correlation; Cost function; Decoding; Detectors; Ultra wideband technology; Vectors; compressive sampling; multiple symbol differential detection; ultra-wideband;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ultra-Wideband (ICUWB), 2012 IEEE International Conference on
  • Conference_Location
    Syracuse, NY
  • ISSN
    2162-6588
  • Print_ISBN
    978-1-4577-2031-4
  • Type

    conf

  • DOI
    10.1109/ICUWB.2012.6340501
  • Filename
    6340501