On variable length codes for iterative source/channel decoding

We focus on a trellis-based decoding technique for variable length codes (VLCs) which does not require any additional side information besides the number of bits in the coded sequence. A bit-level soft-in/soft-out decoder based on this trellis is used as an outer component decoder in an iterative decoding scheme for a serially concatenated source/channel coding system. In contrast to previous approaches using this kind of trellis we do not consider the received sequence as a concatenation of variable length codewords, but as one long code word of a (weak) binary channel code which can be soft-in/soft-out decoded. By evaluating the distance properties of selected variable length codes we show that some codes are more suitable for trellis-based decoding than others. Finally we present simulation results which show the performance of the iterative decoding approach.

[1]  V. Balakirsky Joint source-channel coding with variable length codes , 1997, Proceedings of IEEE International Symposium on Information Theory.

[2]  M. Wada,et al.  Reversible variable length codes , 1995, IEEE Trans. Commun..

[3]  Joachim Hagenauer,et al.  Iterative source/channel-decoding using reversible variable length codes , 2000, Proceedings DCC 2000. Data Compression Conference.

[4]  David J. Miller,et al.  Improved joint source-channel decoding for variable-length encoded data using soft decisions and MMSE estimation , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[5]  Patrick G. Farrell,et al.  Variable-length error-correcting codes , 2000 .

[6]  Richard D. Wesel,et al.  Robust joint Huffman and convolutional decoding , 1999, Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324).

[7]  Victor Buttigieg,et al.  On variable-length error-correcting codes , 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

[8]  John D. Villasenor,et al.  Utilizing soft information in decoding of variable length codes , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[9]  Tamotsu Kasai,et al.  A Method for the Correction of Garbled Words Based on the Levenshtein Metric , 1976, IEEE Transactions on Computers.

[10]  Thomas E. Fuja,et al.  Robust transmission of variable-length encoded sources , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[11]  Andrew J. Viterbi,et al.  Principles of Digital Communication and Coding , 1979 .

[12]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[13]  Joachim Hagenauer,et al.  The turbo principle-tutorial introduction and state of the art , 1997 .

[14]  J. Vaisey,et al.  Joint source-channel decoding of entropy coded Markov sources over binary symmetric channels , 1999, 1999 IEEE International Conference on Communications (Cat. No. 99CH36311).