Chao Tian

TL;DR: In this article, the authors consider the optimality of source-channel separation in networks, and show that such a separation approach is optimal or approximately optimal for a large class of scenarios, namely, when the sources are mutually independent, and each source is needed only at one destination (or at multiple destinations at the same distortion level).

TL;DR: This work provides a complete characterization of the achievable distortion region for the problem of sending a bivariate Gaussian source over bandwidth-matched Gaussian broadcast channels, where each receiver is interested in only one component of the source.

TL;DR: In this paper, the authors considered the problem of side-information scalable (SI-scalable) source coding, where the encoder constructs a two-layer description, such that the receiver with high quality side information will be able to use only the first layer to reconstruct the source in a lossy manner, while the receiving receiver with low quality information will have to receive both layers in order to decode, and provided inner and outer bounds to the rate-distortion region for general discrete memoryless sources.

TL;DR: In this article, the authors considered multiple description (MD) coding for the Gaussian source with K descriptions under the symmetric mean-squared error (MSE) distortion constraints, and provided an approximate characterization of the rate region.

TL;DR: This work considers the storage-retrieval rate tradeoff in private information retrieval systems using a Shannon-theoretic approach and proposes a coding scheme based on random codebook generation, joint typicality encoding, and the binning technique for the canonical two-message two-database case.