Joint turbo decoding and estimation of hidden Markov sources

We describe a joint source-channel scheme for modifying a turbo decoder in order to exploit the statistical characteristics of hidden Markov sources. The basic idea is to treat the trellis describing the hidden Markov source as another constituent decoder which exchanges information with the other constituent decoder blocks. The source block uses as extrinsic information the probability of the input bits that is provided by the constituent decoder blocks. On the other hand, it produces a new estimation of such a probability which will be used as extrinsic information by the constituent turbo decoders. The proposed joint source-channel decoding technique leads to significantly improved performance relative to systems in which source statistics are not exploited and avoids the need to perform any explicit source coding prior to transmission. Lack of a priori knowledge of the source parameters does not degrade the performance of the system, since these parameters can be jointly estimated with turbo decoding.

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

[2]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

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

[4]  L. Baum,et al.  Growth transformations for functions on manifolds. , 1968 .

[5]  Javier Garcia-Frías,et al.  Turbo decoding of hidden Markov sources with unknown parameters , 1998, Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225).

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

[7]  L. Baum,et al.  Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .

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

[9]  J.D. Villasenor,et al.  Simplified methods for combining hidden Markov models and turbo codes , 1999, Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324).

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

[11]  T.E. Fuja,et al.  Channel codes that exploit the residual redundancy in CELP-encoded speech , 1996, IEEE Trans. Speech Audio Process..

[12]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[13]  Dariush Divsalar,et al.  A soft-input soft-output APP module for iterative decoding of concatenated codes , 1997, IEEE Communications Letters.