On quantizer design for distributed source coding of Gaussian vector data with packet loss

Shaminda Subasingha, Manohar Murthi

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

Abstract

Distributed Source Coding (DSC) has been widely studied in applications such as video coding and distributed sensor networks. However, DSC has not been widely explored for low delay and low bit rate applications such as quantization of speech Line Spectral Frequencies (LSFs). This is due to the difficulty of modeling and analyzing the effects of imperfect side information resulting from the previous packet losses, quantization noise and decoding errors. In this paper, we present methods for modeling, analyzing and designing Wyner-Ziv(WZ) quantizers for jointly Gaussian vector data with imperfect side information. In particular, we show the decomposition of the quantizer design problem for the vector data into independent scalar design subproblems. Then we demonstrate the analytical techniques to compute the optimum step size and bit allocation for each scalar dimension to minimize the decoder expected Mean Squared Error(MSE). The simulation results verify the analytical results obtained in this paper.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages1330-1333
Number of pages4
DOIs
StatePublished - Nov 8 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

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Keywords

  • Gaussian pdf
  • Packet loss
  • Wyner-Ziv

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Subasingha, S., & Murthi, M. (2010). On quantizer design for distributed source coding of Gaussian vector data with packet loss. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 1330-1333). [5495436] https://doi.org/10.1109/ICASSP.2010.5495436