View source for Estimation over Communication Networks: Performance Bounds and Achievability Results

{{HTDB paper
| authors = Amir F. Dana, Vijay Gupta, Joao P. Hespanha, Babak Hassibi, Richard M. Murray
| title = Estimation over Communication Networks: Performance Bounds and Achievability Results
| source = Submitted, 2006 Conference on Decision and Control
| year = 2006
| type = Conference Paper
| funding = AFOSR/coop
| url = http://www.cds.caltech.edu/~murray/preprints/dan+06-cdc.pdf
| abstract = 
This paper considers the problem of estimation over
communication networks. Suppose a sensor is taking
measurements of a dynamic 
process. However the process needs to be estimated at a
remote
location connected to the sensor through a network of
communication links that drop
packets stochastically. We provide a framework for
computing the
optimal performance in the sense of expected error
covariance. Using
this framework we characterize the dependency of the
performance on
the topology of the network and the packet dropping
process. For
independent and memoryless packet dropping processes we
find the
steady-state error for some classes of networks and obtain
lower and
upper bounds for the performance of a general network. We
also
illustrate how this framework can be used in the synthesis
of
networks for the purpose of estimation. Finally we find a
necessary
and sufficient condition for the stability of the estimate
error
covariance for general networks with spatially correlated
and Markov
type dropping process. This interesting condition has a
max-cut
interpretation.
| flags = 
| tag = dan+06-cdc
| id = 2006e
}}