ICASSP 2007 - April 15-20, 2007 - Honolulu, Hawai'i, U.S.A.

TUT-9: Joint Source and Channel Decoding: An Idea Whose Time Has Come

Monday Morning, April 16
09:00 - 12:00
Room 323A

Presented by

Pierre Duhamel and Michel Kieffer, CNRS/LSS

Abstract

  1. Introduction

    The tutorial begins by a careful motivation, based on actual applications

    • Context of the work
    • Solutions currently used
      • Example 1 : visophony over IP
      • Example 2 : video broadcasting
      • Example 3 : Multimedia multicasting
    • Structure of a video coder
    • Network adaptation - application layer point of view
  2. Why source and channel joint decoding?

    Then we proceed by a careful description of the mechanism which will allow the JSCD to be undertaken

  3. Identifying redundancy
    • Redundancy due to the spelling
    • Redundancy due to source--VLC probability mismatch
    • Redundancy for a Markov source
    • Redundancy due to the semantic of the source coder
    • Redundancy due to packetization

    Followed by a careful description of the basic tools that will be used

  4. Evidencing the structure of the redundancy
    • Estimators
    • Bit-clock trellis
    • Symbol-clock trellis
  5. A first step for using JSCD in realistic situations

    It is also shown that these basic tools are not sufficient in practical situations, and we show one possible (partial)solution

    • Constraints imposed by the encoder
    • Problem formulation
    • A suboptimal algorithm
    • Methodology
    • Applications
  6. A note on sequential decoding
  7. Iterative decoding -between source and channel decoder-
  8. The global picture: Taking the network into account

    Finally, we show that an efficient solution to the problem requires more insight on the network part.

    • General OSI layers (in short)
    • Mac layer in WIFI
    • Mac layer in DVB-H

      This global picture opens new possibilities

    • CRC at MAC layer used to emulate an erasure channel
      • MPE-FEC of the Mac layer in DVB-H
      • How is it used ?
      • How is it tuned ?
    • CRC used as additional data on the source frame

      and also opens new problems

    • ACK/NACK (CRC, in conjunction with robust decoding)
    • RS, or additional redundancy in the bit stream ? (MDP and robust decoding)
    • What is the best use of redundancy ?
    • Robust decoding of arithmetic codes
      • Introduction on AC
        • Infinite-precision arithmetic coder
        • Finite-precision arithmetic coder
        • Arithmetic codes as JSC codes
      • Trellis-based arithmetic coding and decoding
        • AC interpreted as a state machine
      • Performance analysis of trellis-based AC
        • Free distance
        • Low-complexity evaluation of free distance
        • Asymptotic error bounds
      • Design of robust AC using distance properties
      • Experimental results and discussion
        • Limitation of follow
        • Effect of additional redundancy
        • Optimization of the forbidden symbol
  9. Conclusion

Target Audience

Our intent is to take a typical SP audience, having some knowledge on trellises, channel decoding, and make this audience to understand the problem, the tools for solving it, and have a good insight on the most advance research in this area. All this is connected with practical applications, and is illustrated with simulations of video transmitted through wireless links.

In othert words, the audience must not have a strong background in the Joint source and channel coding area. The tutorial should be understood by a vast majority of Signal Processing people.

Speaker Biographies

Pierre Duhamel (Fellow, IEEE, 1998) was born in France in 1953. He received the Eng. Degree in Electrical Engineering from the National Institute for Applied Sciences (INSA) Rennes, France in 1975, the Dr. Eng. Degree in 1978, and the Doctoratès sciences degree in 1986, both from Orsay University, Orsay, France.

From 1975 to 1980, he was with Thomson-CSF, Paris, France, where his research interests were in circuit theory and signal processing, including digital filtering and analog fault diagnosis. In 1980, he joined the National Research Center in Telecommunications (CNET), Issy les Moulineaux, France, where his research activities were first concerned with the design of recursive CCD filters. Later, he worked on fast algorithms for computing Fourier transforms and convolutions, and applied similar techniques to adaptive filtering, spectral analysis and wavelet transforms. From 1993 to Sept. 2000, he has been professor at ENST, Paris (National School of Engineering in Telecommunications) with research activities focused on Signal processing for Communications. He was head of the Signal and Image processing Department from 1997 to 2000. He is now with CNRS/LSS (Laboratoire de Signaux et Systemes, Gif sur Yvette, France), where he is developing studies in Signal processing for communications (including equalization, iterative decoding, multicarrier systems) and signal/image processing for multimedia applications, including source coding, joint source/channel coding, watermarking, and audio processing.

Dr. Duhamel was chairman of the DSP committee from 1996 to 1998, and a member of the SP for Com committee until 2001. He was an associate Editor of the IEEE Transactions on Signal Processing from 1989 to 1991, an associate Editor for the IEEE Signal Processing Letters, and a guest editor for the special issue of the IEEE Trans. on SP on wavelets.

He was Distiguished lecturer, IEEE, for 1999, and was co-general chair of the 2001 International Workshop on Multimedia Signal Processing, Cannes, France. He will be co-technical chair of ICASSP 06, Toulouse, France. The paper on subspace-based methods for blind equalization, which he co-authored, received the "Best paper award" from the IEEE transactions on SP in 1998. He was awarded the "grand prix France Telecom" by the French Science Academy in 2000.

Michel Kieffer (Member, IEEE, 2003) was born in Sarreguemines, France in 1972. In 1995, he received the Agrégation in Applied Physics at the Ecole Normale Supérieure de Cachan, France. He received a PhD degree in Control and Signal Processing in 1999, and the Habilitation à Diriger des Recherches degree in 2005, both from the Univ Paris-Sud, Orsay, France.

Michel Kieffer is an assistant professor in signal processing for communications at the Univ Paris-Sud and a researcher at the Laboratoire des Signaux et Systèmes, Gif-sur-Yvette, France. His research interests are in joint source-channel coding and decoding techniques for the reliable transmission of multimedia contents. He is also interested in guaranteed parameter and state estimation for systems described by non-linear models.

Michel Kieffer is co-author of more than 60 contributions in journals, conference proceedings, or books. He is one of the co-author of the book Applied Interval Analysis published by Springer-Verlag in 2001.


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