Iterative Source-Channel Decoding Using Symbol-Level Extrinsic Information

Transmission of convolutionally encoded source-codec parameters over noisy channels can benefit from the turbo principle through iterative source-channel decoding. We first formulate a recursive implementation based on sectionalized code trellises for MAP symbol decoding of binary convolutional codes. Performance is further enhanced by the use of an interpolative softbit source decoder that takes into account the channel outputs within an interleaving block. Simulation results indicate that our proposed scheme allows to exchange between its constituent decoders the symbol-level extrinsic information and achieves high robustness against channel noises.