Optimal periodic transmission power schedules for remote estimation of ARMA processes

Title: Optimal periodic transmission power schedules for remote estimation of ARMA processes
Creator: Li, Yuzhe; Quevedo, Daniel E.; Lau, Vincent; Shi, Ling
Relation: ARC.DP0988601 http://purl.org/au-research/grants/arc/DP0988601
Relation: IEEE Transactions on Signal Processing Vol. 61, Issue 24, p. 6164-6174
Publisher Link: http://dx.doi.org/10.1109/TSP.2013.2283838
Publisher: Institute of Electrical and Electronics Engineers
Resource Type: journal article
Date: 2013
Description: We consider periodic sensor transmission power allocation with an average energy constraint. The sensor sends its Kalman filter-based state estimate to the remote estimator through an unreliable link. Dropout probabilities depend on the power level used. To encompass applications where the estimator needs to attend to multiple tasks, we allow for irregular sampling, following a periodic pattern. Using properties of an underlying Markov chain model, we derive an explicit expression for the estimation error covariance. The results are then used to study optimal sensor power scheduling which minimizes the average error covariance.
Subject: Kalman filtering; multi-sampling; networked estimation; power scheduling
Identifier: http://hdl.handle.net/1959.13/1341082
Identifier: uon:28653
Identifier: ISSN:1053-587X
Language: eng
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