TY - JOUR
T1 - Reducing power consumption in a sensor network by information feedback
AU - Kisialiou, Mikalai
AU - Luo, Zhi Quan
PY - 2006
Y1 - 2006
N2 - We study the role of information feedback for the problem of distributed signal tracking/estimation using a sensor network with a fusion center. Assuming that the fusion center has sufficient energy to reliably feed back its intermediate estimates, we show that the sensors can substantially reduce their power consumption by using the feedback information in a manner similar to the stochastic approximation scheme of Robbins-Monro. For the problem of tracking an autoregressive source or estimating an unknown parameter, we quantify the total achievable power saving (as compared to the distributed schemes with no feedback), and provide numerical simulations to confirm the theoretical analysis.
AB - We study the role of information feedback for the problem of distributed signal tracking/estimation using a sensor network with a fusion center. Assuming that the fusion center has sufficient energy to reliably feed back its intermediate estimates, we show that the sensors can substantially reduce their power consumption by using the feedback information in a manner similar to the stochastic approximation scheme of Robbins-Monro. For the problem of tracking an autoregressive source or estimating an unknown parameter, we quantify the total achievable power saving (as compared to the distributed schemes with no feedback), and provide numerical simulations to confirm the theoretical analysis.
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M3 - Conference article
AN - SCOPUS:84862615836
SN - 2219-5491
JO - European Signal Processing Conference
JF - European Signal Processing Conference
T2 - 14th European Signal Processing Conference, EUSIPCO 2006
Y2 - 4 September 2006 through 8 September 2006
ER -