On the iterative approximation of optimal joint source-channel decoding

Joint source-channel decoding is formulated as an estimation problem. The optimal solution is stated and it is shown that it is not feasible in many practical systems due to its complexity. Therefore, a novel iterative procedure for the approximation of the optimal solution is introduced, which is based on the principle of iterative decoding of turbo codes. New analytical expressions for different types of information in the optimal algorithm are used to derive the iterative approximation. A direct comparison of the performance of the optimal algorithm and its iterative approximation is given for a simple transmission system with "short" channel codewords. Furthermore, the performance of iterative joint source-channel decoding is investigated for a more realistic system.

[1]  Javier Garcia-Frías,et al.  Combining hidden Markov source models and parallel concatenated codes , 1997, IEEE Communications Letters.

[2]  N. Gortz,et al.  Joint source channel decoding using bit-reliability information and source statistics , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[3]  Ezio Biglieri,et al.  Joint source and channel coding using turbo codes over rings , 1998, IEEE Trans. Commun..

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

[5]  Nam C. Phamdo,et al.  Optimal detection of discrete Markov sources over discrete memoryless channels - applications to combined source-channel coding , 1994, IEEE Trans. Inf. Theory.

[6]  Joachim Hagenauer.  Source-controlled channel decoding , 1995, IEEE Trans. Commun..

[7]  Patrick Robertson,et al.  Optimal and sub-optimal maximum a posteriori algorithms suitable for turbo decoding , 1997, Eur. Trans. Telecommun..

[8]  Joachim Hagenauer,et al.  A Viterbi algorithm with soft-decision outputs and its applications , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[9]  Alain Glavieux,et al.  Reflections on the Prize Paper : "Near optimum error-correcting coding and decoding: turbo codes" , 1998 .

[10]  Joachim Hagenauer,et al.  Iterative decoding of binary block and convolutional codes , 1996, IEEE Trans. Inf. Theory.

[11]  P. Vary,et al.  Robust speech transmission over noisy channels employing non-linear block codes , 1999, 1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351).

[12]  Peter Vary,et al.  Robust speech decoding: a universal approach to bit error concealment , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  G Norbert.  Joint Source-Channel Decoding by Channel-Coded Optimal Estimation , 2000 .

[14]  Peter Vary,et al.  Joint speech codec parameter and channel decoding of parameter individual block codes (PIBC) , 1999, 1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351).