Robust Consensus in the Presence of Impulsive Channel Noise

Sivaraman Dasarathan, Cihan Tepedelenlioʇlu, Mahesh K. Banavar, Andreas Spanias

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

A distributed average consensus algorithm robust to a wide range of impulsive channel noise distributions is proposed. This work is the first of its kind in the literature to propose a consensus algorithm which relaxes the requirement of finite moments on the communication noise. It is shown that the nodes reach consensus asymptotically to a finite random variable whose expectation is the desired sample average of the initial observations with a variance that depends on the step size of the algorithm and the receiver nonlinear function. The asymptotic performance is characterized by deriving the asymptotic covariance matrix using results from stochastic approximation theory. Simulations corroborate our analytical findings and highlight the robustness of the proposed algorithm.

Original languageEnglish (US)
Article number7054507
Pages (from-to)2118-2129
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume63
Issue number8
DOIs
StatePublished - Apr 15 2015

Keywords

  • Distributed consensus
  • Markov processes
  • asymptotic covariance
  • bounded transmissions
  • impulsive noise
  • sensor networks
  • stochastic approximation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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