Coding perspectives for collaborative estimation over networks

A collaborative distributed estimation problem over a communication constrained network is considered from an information theory perspective. A suitable architecture for the codes for this multiterminal information theory problem is determined under source-channel separation. In particular, distributed source codes in which each node multicasts a different message to each subset of other nodes are studied. This code construction hybridizes 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. An achievable rate distortion region is proved to this problem and its structural properties are studied. Also, this achievable rate region is shown to simplify to the known bounds to some simpler problems.