The duality between information embedding and source coding with side information and some applications

Aspects of the duality between the information-embedding problem and the Wyner-Ziv (1976) problem of source coding with side information at the decoder are developed and used to establish a spectrum new results on these and related problems, with implications for a number of important applications. The single-letter characterization of the information-embedding problem is developed and related to the corresponding characterization of the Wyner-Ziv problem, both of which correspond to optimization of a common mutual information difference. Dual variables and dual Markov conditions are identified, along with the dual role of noise and distortion in the two problems. For a Gaussian context with quadratic distortion metric, a geometric interpretation of the duality is developed. From such insights, we develop a capacity-achieving information-embedding system based on nested lattices. We show the resulting encoder-decoder has precisely the same decoder-encoder structure as the corresponding Wyner-Ziv system based on nested lattices that achieves the rate-distortion limit. For a binary context with Hamming distortion metric, the information-embedding capacity is developed, along with its relationship to the corresponding Wyner-Ziv rate-distortion function. In turn, an information-embedding system for this case based on nested linear codes is constructed having an encoder-decoder that is identical to the decoder-encoder structure for the corresponding system that achieves the Wyner-Ziv rate-distortion limit. Finally, based on these results, a simple layered joint source-channel coding system is developed with a perfectly symmetric encoder-decoder structure. Its application and performance is discussed in a broadcast setting in which there is a need to control the fidelity experienced by different receivers. Among other results, we show that such systems and their multilayer extensions retain attractive optimality properties in the Gaussian-quadratic case, but not in the binary-Hamming case.