Communication scheduling for decentralized state estimation

This paper considers decentralized state estimation subject to communication constraints. A group of agents measure the state of a process and obtain their state estimates by exchanging data with one another. Due to the communication constraint, only a few communication channels are available. The main objective of this paper is to allocate these channels among the agents so as to minimize their average estimation errors. Assuming the agents have the same sensing capability, we provide the optimal allocation strategy for both directed and un-directed communication channels.