Robust distributed active power control technique for IEEE 802.15.4 wireless sensor networks — A quantitative feedback theory approach

Alavi, Seyed Mohammad Mahdi; Walsh, Michael; Hayes, Martin J.

doi:10.1016/j.conengprac.2009.02.001

Cited by 34 publications

(22 citation statements)

References 18 publications

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“…These control-theoretic approaches are based on RSSI measurements and thus suffer from the same robustness issues as [4], [5], [18], [19], [27]- [29] [6], [7], [9], [12], [16], [17] TABLE I TAXONOMY OF TRANSMISSION POWER CONTROL. ATPC. Moreover, these control algorithms are computationally intensive for resource-constrained embedded sensor platforms.…”

Section: Related Workmentioning

confidence: 99%

“…Previous work has suggested that a piecewise linear relationship can be used to approximate the actual power output from a specified power level [4], [8].…”

Section: A Link Modelmentioning

confidence: 99%

“…Control-theoretic approaches have been proposed to deal with TPC in recent literature including robust control [4], [27], [28], model predictive control [29] and Markov chain [5]. These control-theoretic approaches are based on RSSI measurements and thus suffer from the same robustness issues as [4], [5], [18], [19], [27]- [29] [6], [7], [9], [12], [16], [17] TABLE I TAXONOMY OF TRANSMISSION POWER CONTROL. ATPC.…”

Section: Related Workmentioning

confidence: 99%

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Practical control of transmission power for Wireless Sensor Networks

Sha

Hackmann

et al. 2012

2012 20th IEEE International Conference on Network Protocols (ICNP)

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Abstract-Transmission power control (TPC) has the potential to reduce power consumption in Wireless Sensor Networks (WSNs). However, despite a multitude of existing protocols, they still face significant challenges in real-world deployments. A practical TPC protocol must be robust against complex and dynamic wireless properties, and efficient for resource-constrained sensors. This paper presents P-TPC, a practical TPC protocol designed on control-theoretic techniques. P-TPC features a highly efficient controller designed on a dynamic model that combines a theoretical link model with online parameter estimation. P-TPC's robustness and energy savings are demonstrated through trace-driven simulations and real-world experiments in a campus building and residential environments.

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Section: Related Workmentioning

confidence: 99%

“…Previous work has suggested that a piecewise linear relationship can be used to approximate the actual power output from a specified power level [4], [8].…”

Section: A Link Modelmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Practical control of transmission power for Wireless Sensor Networks

Sha

Hackmann

et al. 2012

2012 20th IEEE International Conference on Network Protocols (ICNP)

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“…With this information, the controller minimizes the finite-set constrained cost function (29) 7 In some wireless sensor technologies, transmission power can be selected only from a finite number of power levels. In these cases, the quantization constraint (24) is a system requirement, see also [32]. where 8 (30) quantify the expected estimation quality and the associated energy expenditure.…”

Section: B Cost Functionmentioning

confidence: 99%

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

Quevedo

Åhlén

Østergaard

2010

IEEE Trans. Signal Process.

100

102

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Abstract-We study state estimation via wireless sensors over fading channels. Packet loss probabilities depend upon time-varying channel gains, packet lengths and transmission power levels of the sensors. Measurements are coded into packets by using either independent coding or distributed zero-error coding. At the gateway, a time-varying Kalman filter uses the received packets to provide the state estimates. To trade sensor energy expenditure for state estimation accuracy, we develop a predictive control algorithm which, in an online fashion, determines the transmission power levels and codebooks to be used by the sensors. To further conserve sensor energy, the controller is located at the gateway and sends coarsely quantized power increment commands, only whenever deemed necessary. Simulations based on real channel measurements illustrate that the proposed method gives excellent results.

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“…Consider n fixed points or beacons with Cartesian coordinates (x 1i , x 2i ) with RSSI i (dBm), i = 1,…,n. RSSI i (Alavi et al, 2009) is measured for mobile node communication link i (i = 1,…,n). In Figure 1 trilateration approach is depicted for three beacons example.…”

Section: Indoors Localization Using Rf Trilaterationmentioning

confidence: 99%