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Joint Source-Channel Coding in Dictionary Methods of Lossless Data Compression

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Limitations on memory and resources of communications systems require powerful data compression methods. Decompression of compressed data stream is very sensitive to errors which arise during transmission over noisy channels, therefore error correction coding is also required. One of the solutions to this problem is the application of joint source and channel coding. This paper contains a description of methods of joint source-channel coding based on the popular data compression algorithms LZ'77 and LZSS. These methods are capable of introducing some error resiliency into compressed stream of data without degradation of the compression ratio. We analyze joint source and channel coding algorithms based on these compression methods and present their novel extensions. We also present some simulation results showing usefulness and achievable quality of the analyzed algorithms.
  • Chair of Wireless Communications at Faculty of Electronics and Telecommunications, Poznań University of Technology, Polanka 3, 60-965 Poznań, Poland,
  • [1] W. Szpankowski and S. Lonardi, “Joint source-channel LZ'77 coding,” in IEEE Data Compression Conference, 2003.
  • [2] W. Szpankowski, S. Lonardi, and M. D. Ward, “Error resilient LZ'77 scheme and its analysis,” in International Symposium on Information Theory, 2004.
  • [3] W. Szpankowski, S. Lonardi, and M. D.Ward, “Error resilient LZ'77 data compression: Algorithms, analysis and experiments,” IEEE Transactions on Information Theory, vol. 53, no. 5, May 2007.
  • [4] J. Ziv and A. Lempel, “A universal algorithm for sequential data compression,” IEEE Transaction on Information Theory, May 1977.
  • [5] M. Rodziewicz, “Investigation of source coding supported with channel coding,” Master's thesis, Dept. Electronics and Telecommunications, Poznan University of Technology, Poznan, Poland, 2009.
  • [6] D. Salomon, Data Compression: The Complete Reference. Springer-Verlag, 2004.
  • [7] T. M. Cover and J. A. Thomas, Elements of Information Theory. Wiley & Sons, 2006.
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