Distributed signal estimation in sensor networks where nodes have different interests

  • Authors:

  • Alexander Bertrand;Marc Moonen

  • Affiliations:

  • Department of Electrical Engineering (ESAT-SCD), KU Leuven, University of Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium;Department of Electrical Engineering (ESAT-SCD), KU Leuven, University of Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium

  • Venue:
  • Signal Processing
  • Year:
  • 2012

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Abstract

In this paper, we consider distributed signal estimation in sensor networks where the nodes exchange compressed sensor signal observations to estimate different node-specific signals. In particular, we revisit the so-called distributed adaptive node-specific signal estimation (DANSE) algorithm, which applies to the case where the nodes share a so-called 'common interest', and cast it in the more general setting where the nodes have 'different interests'. We prove existence of an equilibrium state for such a setting by using a result from fixed point theory. By establishing a link between the DANSE algorithm and game theory, we point out that any equilibrium of the DANSE algorithm is a Nash equilibrium of the corresponding game. This provides an intuitive interpretation to the resulting signal estimators. The equilibrium state existence proof also reveals a problem with discontinuities in the DANSE update function, which may result in non-convergence of the algorithm. However, since these discontinuities are identifiable, they can easily be avoided by applying a minor heuristic modification to the algorithm. We demonstrate the effectiveness of this modification by means of numerical examples.