Decentralized detection in sensor networks

Jean François Chamberland, Venugopal V. Veeravalli

Research output: Contribution to journalArticlepeer-review


In this paper, we investigate a binary decentralized detection problem in which a network of wireless sensors provides relevant information about the state of nature to a fusion center. Each sensor transmits its data over a multiple access channel. Upon reception of the information, the fusion center attempts to accurately reconstruct the state of nature. We consider the scenario where the sensor network is constrained by the capacity of the wireless channel over which the sensors are transmitting, and we study the structure of an optimal sensor configuration. For the problem of detecting deterministic signals in additive Gaussian noise, we show that having a set of identical binary sensors is asymptotically optimal, as the number of observations per sensor goes to infinity. Thus, the gain offered by having more sensors exceeds the benefits of getting detailed information from each sensor. A thorough analysis of the Gaussian case is presented along with some extensions to other observation distributions.

Original languageEnglish (US)
Pages (from-to)407-416
Number of pages10
JournalIEEE Transactions on Signal Processing
Issue number2
StatePublished - Feb 2003


  • Bayesian estimation
  • Decentralized detection
  • Sensor network
  • Wireless sensors

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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