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LLOCUS: learning-based localization using crowdsourcing

Authors:

Harsimran Singh,

Samuel RamirezAuthors Info & Claims

Mobihoc '20: Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing

Pages 201 - 210

https://doi.org/10.1145/3397166.3409142

Published: 11 October 2020 Publication History

Abstract

We present LLOCUS, a novel learning-based system that uses mobile crowdsourced RF sensing to estimate the location and power of unknown mobile transmitters in real time, while allowing unrestricted mobility of the crowdsourcing participants. We carefully identify and tackle several challenges in learning and localizing, based on RSS, in such a dynamic environment. We decouple the problem of localizing a transmitter with unknown transmit power into two problems, 1) predicting the power of a transmitter at an unknown location, and 2) localizing a transmitter with known transmit power. LLOCUS first estimates the power of the unknown transmitter and then scales the reported RSS values such that the unknown transmit power problem is transparent to the method of localization. We evaluate LLOCUS using three experiments in different indoor and outdoor environments. We find that LLOCUS reduces the localization error by 17-68% compared to several non-learning methods.

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Cited By

Sallouha HSarkar SKrijestorac ECabric D(2024)REM-U-Net: Deep Learning Based Agile REM Prediction With Energy-Efficient Cell-Free Use CaseIEEE Open Journal of Signal Processing10.1109/OJSP.2024.33785915(750-765)Online publication date: 2024
https://doi.org/10.1109/OJSP.2024.3378591
Mitchell FWang JBhaskara AKasera S(2024)Utilizing Confidence in Localization Predictions for Improved Spectrum Management2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)10.1109/DySPAN60163.2024.10632736(483-492)Online publication date: 13-May-2024
https://doi.org/10.1109/DySPAN60163.2024.10632736
Mitchell FSmith JSarkar SPatwari NBhaskara AKasera S(2024)Localizing Spectrum Offenders Using CrowdsourcingNetwork Security Empowered by Artificial Intelligence10.1007/978-3-031-53510-9_9(237-264)Online publication date: 24-Feb-2024
https://doi.org/10.1007/978-3-031-53510-9_9
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Index Terms

LLOCUS: learning-based localization using crowdsourcing
1. Networks

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cover image ACM Conferences

Mobihoc '20: Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing

October 2020

384 pages

ISBN:9781450380157

DOI:10.1145/3397166

General Chairs:
Tommaso Melodia
Northeastern University
,
Eylem Ekici
The Ohio State University
,
Program Chairs:
Alhussein Abouzeid
Rensselaer Polytechnic Institute
,
Minghua Chen
City University of Hong Kong

Copyright © 2020 ACM.

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 11 October 2020

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Mobihoc '20

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SIGMOBILE

Mobihoc '20: The Twenty-first ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing

October 11 - 14, 2020

Virtual Event, USA

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Overall Acceptance Rate 296 of 1,843 submissions, 16%

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Cited By

Sallouha HSarkar SKrijestorac ECabric D(2024)REM-U-Net: Deep Learning Based Agile REM Prediction With Energy-Efficient Cell-Free Use CaseIEEE Open Journal of Signal Processing10.1109/OJSP.2024.33785915(750-765)Online publication date: 2024
https://doi.org/10.1109/OJSP.2024.3378591
Mitchell FWang JBhaskara AKasera S(2024)Utilizing Confidence in Localization Predictions for Improved Spectrum Management2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)10.1109/DySPAN60163.2024.10632736(483-492)Online publication date: 13-May-2024
https://doi.org/10.1109/DySPAN60163.2024.10632736
Mitchell FSmith JSarkar SPatwari NBhaskara AKasera S(2024)Localizing Spectrum Offenders Using CrowdsourcingNetwork Security Empowered by Artificial Intelligence10.1007/978-3-031-53510-9_9(237-264)Online publication date: 24-Feb-2024
https://doi.org/10.1007/978-3-031-53510-9_9
Mitchell FSmith PBhaskara AKasera SGunduz DMalekzadeh MÖnen MSagduyu YShi YZhang J(2023)Exploring Adversarial Attacks on Learning-based LocalizationProceedings of the 2023 ACM Workshop on Wireless Security and Machine Learning10.1145/3586209.3591398(15-20)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1145/3586209.3591398
Mitchell FBaset APatwari NKasera SBhaskara AJadliwala M(2022)Deep Learning-based Localization in Limited Data RegimesProceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning10.1145/3522783.3529529(15-20)Online publication date: 19-May-2022
https://dl.acm.org/doi/10.1145/3522783.3529529
Smith PLuong ASarkar SSingh HSingh APatwari NKasera SDerr K(2021)A Novel Software Defined Radio for Practical, Mobile Crowd-sourced Spectrum SensingIEEE Transactions on Mobile Computing10.1109/TMC.2021.3107409(1-1)Online publication date: 2021
https://doi.org/10.1109/TMC.2021.3107409

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