Sign-assisted precoding for joint decentralized detection and estimation in WSNs

Jun Fang, Xiaoying Li, Hongbin Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider a joint decentralized detection and estimation problem in which a number of sensor nodes collaborate to detect and estimate an unknown deterministic vector signal. To cope with the power/bandwidth constraints inherent in wireless sensor networks (WSNs), each sensor compresses its observations using a linear precoder. The compressed messages are transmitted to the fusion center (FC), where a global decision is made by resorting to a generalized likelihood ratio test (GLRT), and a maximum likelihood (ML) estimate of the signal is formed if the signal is detected. We propose a sign-assisted random precoding scheme which utilizes the knowledge of the plus/minus signs of the signal components. Performance analysis shows that the signassisted scheme is more effective than the energy detector in detecting weak signals that are buried in noise. Specifically, it outperforms the energy detector when the observation signal-to-noise ratio (SNR) is less than 1/(π-2).

Original languageEnglish
Title of host publication2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings
Pages384-388
Number of pages5
DOIs
StatePublished - 2013
Event2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Beijing, China
Duration: 6 Jul 201310 Jul 2013

Publication series

Name2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings

Conference

Conference2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013
Country/TerritoryChina
CityBeijing
Period6/07/1310/07/13

Keywords

  • Decentralized detection
  • error exponent
  • precoding design
  • wireless sensor networks (WSNs)

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