Design and analysis of optimal noisy channel quantization with random index assignment

  • Authors:

  • Xiang Yu;Haiquan Wang;En-Hui Yang

  • Affiliations:

  • Slipstream, Research In Motion Limited, Waterloo, ON, Canada and Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;College of Communication Engineering, Hangzhou Dianzi University, Xiasha, Hangzhou, China and Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2010

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Abstract

This paper studies the design of vector quantization on noisy channels and its high rate asymptotic performance. Given a tandem source-channel coding system with vector quantization, block channel coding, and random index assignment, a closed-form formula is first derived for computing the average end-to-end distortion (EED) of the system, which reveals a structural factor called the scatter factor of a noisy channel quantizer. Based on this formula, we propose a noisy-channel quantization design method by minimizing the EED. Experiments and simulations show that quantizers jointly designed with channel conditions significantly reduce the EED when compared with quantizers designed separately without reference to channel conditions, which reveals a practical and effective design for noisy-channel quantization as to simplify the channel model by considering a random index assignment. Furthermore, we have presented the high rate asymptotic analysis of the EED for the tandem system, while convergence analysis of the iterative algorithm is included in the Appendix.