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Estimation over Communication Networks: Performance Bounds and Achievability Results

Dana, A. F. and Gupta, V. and Hespanha, J. P. and Hassibi, B. and Murray, R. M. (2007) Estimation over Communication Networks: Performance Bounds and Achievability Results. In: American Control Conference (ACC 2007), New York, NY, 11-13 July 2007. IEEE , Piscataway, NJ, pp. 3450-3455. ISBN 1-4244-0989-6. https://resolver.caltech.edu/CaltechAUTHORS:DANacc07

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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. 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.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/ACC.2007.4282933DOIUNSPECIFIED
ORCID:
AuthorORCID
Murray, R. M.0000-0002-5785-7481
Additional Information:© Copyright 2007 IEEE. Reprinted with permission. [Posted online: 2007-07-30]
Record Number:CaltechAUTHORS:DANacc07
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:DANacc07
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9068
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:25 Oct 2007
Last Modified:02 Oct 2019 23:56

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