• DocumentCode
    2512164
  • Title

    Joint states dimension reduction and quantizer design for estimation under communication constraints

  • Author

    Ying, Shen ; Hui, Zhang

  • Author_Institution
    Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China
  • fYear
    2011
  • fDate
    21-23 Oct. 2011
  • Firstpage
    390
  • Lastpage
    395
  • Abstract
    The problem of joint states dimension reduction and quantizer design under communication constraints was discussed for states estimation in quantized linear dynamic systems. In order to meet the requirements of transmit power constraint and the constraints of number and bandwidth of the parallel channels, the structure of DPCM (differential pulse code modulation) was adopted to produce the quantized innovation as the transmitted signal, and the states dimension reduction and quantizer were designed jointly under the MMSE (minimum mean square estimation error) criterion of filtering at receiver. Analytical analysis and simulation results show that, the estimation performance of the filter at receiver is optimal under communication constraints when the proposed dimension reduction method and the optimal quantizer are applied.
  • Keywords
    differential pulse code modulation; estimation theory; filtering theory; mean square error methods; quantisation (signal); state estimation; DPCM; MMSE; analytical analysis; analytical simulation; communication constraints estimation; differential pulse code modulation; dimension reduction method; filtering; joint states dimension reduction; minimum mean square estimation error criterion; optimal quantizer; parallel channels; performance estimation; quantized innovation; quantized linear dynamic systems; quantizer design; receiver; states estimation; transmit power constraint; transmitted signal; Bandwidth; Covariance matrix; Estimation error; Noise; Quantization; Technological innovation; bandwidth constraint; communication constraint; quantized linear system; states dimension reduction; transmit power constraint;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Problem-Solving (ICCP), 2011 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4577-0602-8
  • Electronic_ISBN
    978-1-4577-0601-1
  • Type

    conf

  • DOI
    10.1109/ICCPS.2011.6092294
  • Filename
    6092294