Filtering Over Non-Gaussian Channels: The Role of Anytime Capacity

Filtering over noisy channels is of interest in many network applications, in which a node infers a time-varying state by using messages received from another node that can observe such a state. This letter explores filtering with general models for state disturbance and communication channels by deriving a sufficient condition for which the estimation error is bounded. Specifically, the sufficient condition is expressed in terms of anytime capacity, a notion that characterizes the maximum sequential communication rate. The joint design of encoder and estimator with bounded estimation error is also presented.

Automated summary

This letter explores the problem of filtering over noisy channels and derives a sufficient condition to bound the estimation error. The joint design of encoder and estimator with bounded estimation error is also presented.