TY - GEN
T1 - Energy-efficient joint estimation in sensor networks
T2 - 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
AU - Cui, Shuguang
AU - Xiao, Jin Jun
AU - Goldsmith, Andrea J.
AU - Luo, Zhi-Quan
AU - Poor, H. Vincent
PY - 2005
Y1 - 2005
N2 - Sensor networks in which energy is a limited resource so that energy consumption must be minimized for the intended application are considered. In this context, an energy-efficient method for the joint estimation of an unknown analog source under a given distortion constraint is proposed. The approach is purely analog, in which each sensor simply amplifies and forwards the noise-corrupted analog observation to the fusion center for joint estimation. The total transmission power across all the sensor nodes is minimized while satisfying a distortion requirement on the joint estimate. The energy efficiency of this analog approach is compared with previously proposed digital approaches with and without coding. It is shown in our simulation that the analog approach is more energy-efficient than the digital system without coding, and in some cases outperforms the digital system with optimal coding.
AB - Sensor networks in which energy is a limited resource so that energy consumption must be minimized for the intended application are considered. In this context, an energy-efficient method for the joint estimation of an unknown analog source under a given distortion constraint is proposed. The approach is purely analog, in which each sensor simply amplifies and forwards the noise-corrupted analog observation to the fusion center for joint estimation. The total transmission power across all the sensor nodes is minimized while satisfying a distortion requirement on the joint estimate. The energy efficiency of this analog approach is compared with previously proposed digital approaches with and without coding. It is shown in our simulation that the analog approach is more energy-efficient than the digital system without coding, and in some cases outperforms the digital system with optimal coding.
UR - http://www.scopus.com/inward/record.url?scp=33646801980&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2005.1416116
DO - 10.1109/ICASSP.2005.1416116
M3 - Conference contribution
AN - SCOPUS:33646801980
SN - 0780388747
SN - 9780780388741
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 745
EP - 748
BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 March 2005 through 23 March 2005
ER -