2015
DOI: 10.1016/j.automatica.2015.02.019
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Data-driven power control for state estimation: A Bayesian inference approach

Abstract: We consider sensor transmission power control for state estimation, using a Bayesian inference approach. A sensor node sends its local state estimate to a remote estimator over an unreliable wireless communication channel with random data packet drops. As related to packet dropout rate, transmission power is chosen by the sensor based on the relative importance of the local state estimate. The proposed power controller is proved to preserve Gaussianity of local estimate innovation, which enables us to obtain a… Show more

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Cited by 37 publications
(12 citation statements)
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References 21 publications
(61 reference statements)
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“…were used in [10,44,45,48,49], and that Assumption 1-(ii) was used in [42]. From Assumption 1-(iv), whether or not the data sent by the sensor is successfully received by the remote estimator is indicated by a sequence {γ k } k∈N of random variables, where…”
Section: Wireless Communication Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…were used in [10,44,45,48,49], and that Assumption 1-(ii) was used in [42]. From Assumption 1-(iv), whether or not the data sent by the sensor is successfully received by the remote estimator is indicated by a sequence {γ k } k∈N of random variables, where…”
Section: Wireless Communication Modelmentioning
confidence: 99%
“…The effects of fading has been taken into account in networked control systems [37][38][39][40]. There are works that are concerned with transmission power management for state estimation [41][42][43][44][45][46][47]. The power allocated to transmission affects the probability of successful reception of the measurement, thus affecting the estimation performance.…”
mentioning
confidence: 99%
“…Recently, this problem has received significant attention (see, e.g., [1]- [4] and the references therein). Till now, plenty of efforts have been made towards the estimation under a single sensor case [5]- [7]. However, the stability analysis of the state estimator according to measurements send from multiple sensors through a lossy network is more difficult.…”
Section: Introductionmentioning
confidence: 99%
“…A covariance-based TPC mechanism for the estimation outage minimization problem over a fading channel is investigated in [4]. A measurement-based TPC mechanism for estimation over a fading channel when the state estimate is transmitted is proposed in [5]. A study on the joint design of an estimator and a TPC mechanism for estimation (without considering the measurement noise) over a fading channel with an infinite horizon average cost function is carried out in [6].…”
Section: Introductionmentioning
confidence: 99%