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Stochastic packet scheduling for optimal parameter estimation
KTH, School of Electrical Engineering (EES), Automatic Control.
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2016 (English)In: Proceedings of the IEEE Conference on Decision and Control, 2016, 3057-3062 p.Conference paper (Refereed)Text
Abstract [en]

In this paper we consider optimal parameter estimation with a constrained packet transmission rate. Due to the limited battery power and the traffic congestion over a large sensor network, each sensor is required to discard some packets and save transmission times. We propose a packet-driven sensor scheduling policy such that the sensor transmits only the important measurements to the estimator. Unlike the existing deterministic scheduler in [1], our stochastic packet scheduling is novelly designed to maintain the computational simplicity of the resulting maximum-likelihood estimator (MLE). This results in a nice feature that the MLE is still able to be recursively computed in a closed form, and the Cramér-Rao lower bound (CRLB) can be explicitly evaluated. Moreover, an optimization problem is formulated and solved to obtain the optimal parameters of the scheduling policy under which the estimation performance is comparable to the standard MLE (with full measurements) even with a moderate transmission rate. Numerical simulations are included to show the effectiveness.

Place, publisher, year, edition, pages
2016. 3057-3062 p.
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-188283DOI: 10.1109/CDC.2015.7402678ScopusID: 2-s2.0-84962033989ISBN: 9781479978861OAI: diva2:936777
54th IEEE Conference on Decision and Control, CDC 2015, 15 December 2015 through 18 December 2015

QC 20160614

Available from: 2016-06-14 Created: 2016-06-09 Last updated: 2016-06-14Bibliographically approved

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Wu, Junfeng
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