Enabling IoT self-localization using ambient 5G mmWave signals

Junfeng Guan, Suraj Jog, Sohrab Madani, Ruochen Lu, Songbin Gong, Deepak Vasisht, Haitham Hassanieh

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

Abstract

The small cell size, wide bandwidth, and MIMO antenna arrays in 5G mmWave networks provide great opportunities for IoT localization. However, low-power and low-cost IoT devices are incapable of leveraging these benefits. We present mm-ISLA: a system that enables IoT nodes to localize themselves using ambient 5G mmWave signals without any coordination with the base stations. mm-ISLA leverages MEMS Spike-Train filters to access the wideband 5G signals and estimates the Angle of Departure from the base station MIMO antenna arrays to accurately localize the IoT nodes.

Original languageEnglish (US)
Title of host publicationSIGCOMM 2022 Demos and Posters - Proceedings of the 2022 SIGCOMM 2022 Poster and Demo Sessions, Part of SIGCOMM 2022
PublisherAssociation for Computing Machinery
Pages49-51
Number of pages3
ISBN (Electronic)9781450394345
DOIs
StatePublished - Aug 22 2022
Event2022 ACM Special Interest Group on Data Communication Conference, SIGCOMM 2022 - Amsterdam, Netherlands
Duration: Aug 22 2022Aug 26 2022

Publication series

NameSIGCOMM 2022 Demos and Posters - Proceedings of the 2022 SIGCOMM 2022 Poster and Demo Sessions, Part of SIGCOMM 2022

Conference

Conference2022 ACM Special Interest Group on Data Communication Conference, SIGCOMM 2022
Country/TerritoryNetherlands
CityAmsterdam
Period8/22/228/26/22

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Computer Networks and Communications

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