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A collaborative distributed estimation problem over a communication constrained network is considered from an information theory perspective. It is shown that the distributed estimation problem is related to multi-terminal information theory and a suitable architecture for the codes for this multi-terminal information theory problem is determined under source-channel separation. In particular, distributed source codes in which each node multicasts a different messages to each subset of other nodes are studied. This code construction hybridizes two important families of source codes: multiple description codes and codes for the CEO problem. The goal of this paper is to determine the fundamental relationship between the multicast communication rates and estimation performance obtainable, which is embodied in the rate distortion region for such distributed source codes.
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