Fusion of quantized data for Bayesian estimation aided by controlled noise

Yujiao Zheng, Ruixin Niu, Pramod K. Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we consider a Bayesian estimation problem in a sensor network where the local sensor observations are quantized before their transmission to the fusion center (FC). Inspired by Widrow's statistical theory on quantization, at the FC, instead of fusing the quantized data directly, we propose to fuse the post-processed data obtained by adding independent controlled noise to the received quantized data. The injected noise acts like a low-pass filter in the characteristic function (CF) domain such that the output is an approximation of the original raw observation. The optimal minimum mean squared error (MMSE) estimator and the posterior Cramér-Rao lower bound for this estimation problem are derived. Based on the Fisher information, the optimal controlled Gaussian noise and the optimal bit allocation are obtained. In addition, a near-optimal linear MMSE estimator is derived to reduce the computational complexity significantly.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages6491-6495
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • Bayesian estimation
  • Fisher information
  • bit allocation
  • data fusion
  • quantization
  • sensor networks

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Zheng, Y., Niu, R., & Varshney, P. K. (2013). Fusion of quantized data for Bayesian estimation aided by controlled noise. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (pp. 6491-6495). [6638916] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6638916