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Decentralized Subspace Tracking via Gossiping

  • Lin Li
  • Xiao Li
  • Anna Scaglione
  • Jonathan H. Manton
Part of the Lecture Notes in Computer Science book series

Abstract

We consider a fully decentralized model for adaptively tracking the signal’s principal subspace, which arises in multi-sensor array detection and estimation problems. Our objective is to equip the network of dispersed sensors with a primitive for online spectrum sensing, which does not require a central fusion node. In this model, each node updates its local subspace estimate with its received data and a weighted average of the neighbors’ data. The quality of the estimate is measured by the total subspace mismatch of the individual subspace component estimates, which converge asymptotically in the Lyapunov sense.

Keywords

Wireless Sensor Network Cognitive Radio Signal Subspace Generalize Likelihood Ratio Test Narrowband Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Lin Li
    • 1
  • Xiao Li
    • 1
  • Anna Scaglione
    • 1
  • Jonathan H. Manton
    • 2
  1. 1.University of CaliforniaDavisUSA
  2. 2.University of MelbourneAustralia

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