Abstract

This paper introduces diffusion adaptation strategies over distributed networks with nonlinear transmissions, motivated by the necessity for bounded transmit power. Local information is exchanged in real-time with neighboring nodes in order to estimate a common parameter vector via constrained nonlinear transmissions, using an adaptive learning algorithm. We propose nonlinear diffusion strategies for such an adaptive estimation. We will study convergence properties of the proposed algorithm in the mean and the mean-square sense. Simulations support the performance analysis and show that the proposed algorithm performs close to the linear case with the added advantage of power savings.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Communications, ICC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6707-6711
Number of pages5
ISBN (Electronic)9781467364324
DOIs
StatePublished - Sep 9 2015
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: Jun 8 2015Jun 12 2015

Publication series

NameIEEE International Conference on Communications
Volume2015-September
ISSN (Print)1550-3607

Other

OtherIEEE International Conference on Communications, ICC 2015
CountryUnited Kingdom
CityLondon
Period6/8/156/12/15

Keywords

  • adaptive networks
  • bounded transmission
  • consensus
  • distributed sensor networks
  • nonlinear diffusion

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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