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Reliable computation of nomographic functions over Gaussian multiple-access channels

  • Technische Universität Berlin
  • Technical University of Munich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In this paper, a wireless sensor network is considered in which the objective is not to communicate individual sensor readings over a Gaussian multiple-access channel to a fusion center but rather to reliably compute some nomographic function thereof. Nomographic functions are exactly those multivariate functions that can be represented as a post-processed sum of pre-processed sensor readings. This special structure permits the utilization of the interference property of the Gaussian multiple-access channel for computing some nomographic functions at significantly higher rates than those achievable with traditional schemes. In this paper, a corresponding coding scheme is presented that protects the sum of pre-processed sensor readings against the channel noise by letting each node use the same nested lattice code.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4814-4818
Number of pages5
DOIs
StatePublished - 18 Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • Distributed computation
  • multiple-access channel
  • nested lattice codes
  • nomographic functions
  • sensor networks

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