Energy Efficient State Estimation With Wireless Sensors Through the Use of Predictive Power Control and Coding

Quevedo, Daniel E.; Åhlén, Anders; Østergaard, Jan

doi:10.1109/tsp.2010.2050883

Cited by 100 publications

(102 citation statements)

References 38 publications

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“…Furthermore, the transmission power available to the individual sensors will also be constrained in magnitude. Thus, power control design involves a trade-off between transmission error probabilities (and, thus, state estimation accuracy) and energy consumption, see also Quevedo et al (2010). Whilst it is indeed important to balance state estimation accuracy against the power used, it is essential to allocate enough power to the sensor nodes so that exponentially boundedness in norm of the state estimation covariance matrix P (k) can be guaranteed.…”

Section: Control Of Transmission Powersmentioning

confidence: 99%

See 1 more Smart Citation

On Kalman Filtering with Fading Wireless Channels Governed by Power Control

Quevedo

Åhlén

Leong

et al. 2011

IFAC Proceedings Volumes

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We study stochastic stability for Kalman filtering over fading wireless channels where variable channel gains are counteracted by the use of power control to alleviate the effects of packet drops. The Kalman filter and the controller are located at a single gateway which acquires data from the wireless sensors. We establish sufficient conditions which ensure that the Kalman filter covariance matrix is exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing optimal power allocation laws which minimize the total sensor power budget. In deriving the optimal power allocation laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.

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Section: Control Of Transmission Powersmentioning

confidence: 99%

“…This was considered in the context of state estimation with power controlled sensor data transmitted over fading channels, e.g., in Quevedo et al (2010).…”

Section: Introductionmentioning

confidence: 99%

On Kalman Filtering with Fading Wireless Channels Governed by Power Control

Quevedo

Åhlén

Leong

et al. 2011

IFAC Proceedings Volumes

Self Cite

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“…Therefore, it is quite necessary to find some new strategies for lowering transmission delay. [8] The transmission delay will be increased up to 12 time unit; the transmission delay will be very long and approach to infinite. The transmission Delay decreases from 4 time unit.…”

Section: Resultsmentioning

confidence: 99%

Comparison and Analysis of Power Loss Channel and Delay Channel for Dynamic Wireless Network

Kaur¹,

Kumar²,

Shrma³

2011

IJCA

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In this paper we contrast wireless network for power loss channel and delay channel used for data transmission. The topology composed of dynamic wireless composites whose position is set by random function and use Zigbee technology for data transmission with RREQ protocols at varying range of transmission of 300, 400 and 500 units. Paper contrast different wireless channel with different wireless protocols in different conditions and concludes to specific result at particular condition.

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“…, k of equal length. 5 These k bitstreams (whose union yields b t (k)) are now considered as input to an (M, k)-erasure code, whose M outputs are denoted by φ …”

Section: Combining Ppc-and Fec-based Mdsmentioning

confidence: 99%

“…To further illustrate the usefulness of the above approach, consider the case where M = 5 and where the decoder receives three packets say s t (2), s t (3), and s t (5). Then from say s t (2), we first recover φ (2) t (1), which is in fact identical toũ t (1).…”

Section: Combining Ppc-and Fec-based Mdsmentioning

confidence: 99%

Multiple descriptions for packetized predictive control

Østergaard

Quevedo

2016

EURASIP J. Adv. Signal Process.

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In this paper, we propose to use multiple descriptions (MDs) to achieve a high degree of robustness towards random packet delays and erasures in networked control systems. In particular, we consider the scenario, where a data-rate limited channel is located between the controller and the plant input. This forward channel also introduces random delays and dropouts. The feedback channel from the plant output to the controller is assumed noiseless. We show how to design MDs for packetized predicted control (PPC) in order to enhance the robustness. In the proposed scheme, a quantized control vector with future tentative control signals is transmitted to the plant at each discrete time instant. This control vector is then transformed into M redundant descriptions (packets) such that when receiving any 1 ≤ J ≤ M packets, the current control signal as well as J − 1 future control signals can be reliably reconstructed at the plant side. For the particular case of LTI plant models and i.i.d. channels, we show that the overall system forms a Markov jump linear system. We provide conditions for mean square stability and derive upper bounds on the operational bit rate of the quantizer to guarantee a desired performance level. Simulations reveal that a significant gain over conventional PPC can be achieved when combining PPC with suitably designed MDs.

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Energy Efficient State Estimation With Wireless Sensors Through the Use of Predictive Power Control and Coding

Cited by 100 publications

References 38 publications

On Kalman Filtering with Fading Wireless Channels Governed by Power Control

On Kalman Filtering with Fading Wireless Channels Governed by Power Control

Comparison and Analysis of Power Loss Channel and Delay Channel for Dynamic Wireless Network

Multiple descriptions for packetized predictive control

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