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We investigate whether uncoded schemes are optimal for Gaussian sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian sources on a Gaussian broadcast channel where each receiver is interested in reconstructing only one source component (or one specific linear function of the sources) under the mean squared error distortion measure;...
We 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. More precisely, for lossy coding of memoryless sources in a network, when the sources are mutually independent, and each source is needed only at one destination (or at multiple destinations at the same distortion level),...
In multiresolution coding a source sequence is encoded into a base layer and a refinement layer. The refinement layer, constructed using a conditional codebook, is in general not decodable without the correct reception of the base layer. By relating multiresolution coding with multiple description coding, we show that it is in fact possible to construct multiresolution codes in certain ways so that...
We study the problem of multiple description coding for binary sources with Hamming distortion measure. The distortion region for the no excess rate case is explicitly characterized. Furthermore, experimental results show that the boundary points of the distortion region can be approached using a sequential coding scheme based on low-density generator matrix codes.
This work addresses practical multiple description coding for uniform binary sources in the no excess sum-rate case. For this case Zhang and Berger have shown that the EGC* region defined by El Gamal and Cover coincides with a portion of the boundary of the MD rate-distortion region, and proposed a construction of the auxiliary variables U and V to achieve this bound. We introduce a sequential coding...
Recently low-density generator matrix (LDGM) codes along with various message-passing algorithms (e.g., survey propagation algorithm) have been used for lossy source coding. In contrast with most prior work which has focused exclusively on uniformly distributed sources, we address the problem of lossy coding for sources with arbitrary distributions. Built upon the idea of approximating the optimal...
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