Power scheduling of universal decentralized estimation in sensor networks

Jin Jun Xiao, Shuguang Cui, Zhi Quan Luo, Andrea J. Goldsmith

Research output: Contribution to journalArticlepeer-review

324 Scopus citations


We consider the optimal power scheduling problem for the decentralized estimation of a noise-corrupted deterministic signal in an inhomogeneous sensor network. Sensor observations are first quantized into discrete messages, then transmitted to a fusion center where a final estimate is generated. Supposing that the sensors use a universal decentralized quantization/estimation scheme and an uncoded quadrature amplitude modulated (QAM) transmission strategy, we determine the optimal quantization and transmit power levels at local sensors so as to minimize the total transmit power, while ensuring a given mean squared error (mse) performance. The proposed power scheduling scheme suggests that the sensors with bad channels or poor observation qualities should decrease their quantization resolutions or simply become inactive in order to save power. For the remaining active sensors, their optimal quantization and transmit power levels are determined jointly by individual channel path losses, local observation noise variance, and the targeted mse performance. Numerical examples show that in inhomogeneous sensing environment, significant energy savings is possible when compared to the uniform quantization strategy.

Original languageEnglish (US)
Pages (from-to)413-422
Number of pages10
JournalIEEE Transactions on Signal Processing
Issue number2
StatePublished - Feb 2006

Bibliographical note

Funding Information:
Manuscript received July 3, 2004; revised April 5, 2005. This work was supported in part by the Natural Sciences and Engineering Research Council of Canada by Grant OPG0090391, by the Canada Research Chair Program, by the National Science Foundation by Grant DMS-0312416, by funds from National Semiconductor, and by the Alfred P. Sloan Foundation. This work was presented in part at the IEEE First Conference on Sensor and Ad Hoc Communications and Networks, Santa Clara, CA, October 2004. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Zidong Wang.


  • Distributed estimation
  • Inhomogeneous quantization
  • Power scheduling
  • Sensor networks


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