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Designing a cloud-based infrastructure for spectrum sensing: A case study for indoor spaces

  • Stony Brook University

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

7 Scopus citations

Abstract

We argue that spectrum sensing on mobile clients will be both necessary and feasible if we wish to manage the white space spectrum optimally in indoor spaces.We demonstrate the necessity with a set of empirical measurements showing the need for fine grained sensing. We demonstrate the feasibility by building a spectrum sensing infrastructure that collects measurements from sensing devices to analyze and better use spectrum resources. The infrastructure consists of mobile spectrum sensors that are built using DTV receiver dongles interfaced with Android-based mobile devices and a cloud-based central server to manage such sensing devices. We also show results about resource consumption (energy, network overhead) involved in operating such sensors. The vision is ultimately creating a system where mobile devices perform part-time spectrum sensing in a coordinated fashion under the control of a central spectrum manager. We lay out the research challenges based on our initial prototyping and benchmarking experience.

Original languageEnglish
Title of host publicationProceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages17-24
Number of pages8
ISBN (Electronic)9781509014590
DOIs
StatePublished - Aug 8 2016
Event12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016 - Washington, United States
Duration: May 26 2016May 28 2016

Publication series

NameProceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016

Conference

Conference12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016
Country/TerritoryUnited States
CityWashington
Period05/26/1605/28/16

Keywords

  • Dynamic spectrum access
  • Mobile spectrum sensing
  • White space

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