Energy-efficient sensing and communication of parallel Gaussian sources

Xi Liu, Osvaldo Simeone, Elza Erkip

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Energy efficiency is a key requirement in the design of wireless sensor networks. While most theoretical studies only account for the energy requirements of communication, the sensing process, which includes measurements and compression, can also consume comparable energy. In this paper, the problem of sensing and communicating parallel sources is studied by accounting for the cost of both communication and sensing. In the first formulation of the problem, the sensor has a separate energy budget for sensing and a rate budget for communication, while, in the second, it has a single energy budget for both tasks. Furthermore, in the second problem, each source has its own associated channel. Assuming that sources with larger variances have lower sensing costs, the optimal allocation of sensing energy and rate that minimizes the overall distortion is derived for the first problem. Moreover, structural results on the solution of the second problem are derived under the assumption that the sources with larger variances are transmitted on channels with lower noise.

Original languageEnglish (US)
Title of host publication2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012
Pages1341-1345
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE International Symposium on Information Theory, ISIT 2012 - Cambridge, MA, United States
Duration: Jul 1 2012Jul 6 2012

Publication series

NameIEEE International Symposium on Information Theory - Proceedings

Other

Other2012 IEEE International Symposium on Information Theory, ISIT 2012
CountryUnited States
CityCambridge, MA
Period7/1/127/6/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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    Liu, X., Simeone, O., & Erkip, E. (2012). Energy-efficient sensing and communication of parallel Gaussian sources. In 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012 (pp. 1341-1345). [6283478] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2012.6283478