Successive refinement for the Wyner-Ziv problem and layered code design

We examine successive refinement for the Wyner-Ziv problem described in a recent paper by Steinberg and Merhav, where the authors showed that if the side information for all stages is identical, then the jointly Gaussian source with squared error distortion measure is successively refinable. We first extend this result to the case where the difference between the source and the side information is Gaussian and independent of the side information. As a byproduct, we give an alternative proof that the Wyner-Ziv problem for these sources has no rate loss-a result that was recently shown by Pradhan et al. through invoking the duality between the Gaussian Wyner-Ziv problem and the Costa problem. We then perform layered Wyner-Ziv code design for this general type of source based on nested scalar quantization, bit-plane coding, and low-density parity check (LDPC) code-based Slepian-Wolf coding (source coding with side information). We show that density evolution can be used to analyze the Slepian-Wolf code performance, provided that certain symmetry conditions, which have been dubbed dual symmetry, are satisfied by the hypothetical channel between the source and the side information. We also show that the dual symmetry condition is indeed satisfied by the hypothetical channel in our Slepian-Wolf coding setup. This justifies the use of density evolution in our LDPC code-based Slepian-Wolf code design for Wyner-Ziv coding. For the jointly Gaussian source, our layered coder performs 1.29 to 3.45 dB from the Wyner-Ziv bound for rates ranging from 0.47 to 4.68 bits per sample. When the side information is Laplacian and the source equals the side information plus an independent Gaussian noise term, our layered coder performs 1.33 to 3.90 dB from the Wyner-Ziv bound for rates ranging from 0.48 to 4.64 bits per sample.