research-article

Batch Localization Based on OFDMA Backscatter

Authors:

Xinbing WangAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 3, Issue 1

Article No.: 25, Pages 1 - 25

https://doi.org/10.1145/3314412

Published: 29 March 2019 Publication History

Abstract

OFDMA Wi-Fi backscatter can significantly improve the communication efficiency and meanwhile maintain ultra-low power consumption; however, the ground-up reworking on the core mechanism of traditional Wi-Fi system revolutionizes the basis of many existing Wi-Fi based mechanisms. In this paper, we explore how localization can be realized based on OFDMA backscatter, where a batch localization mechanism utilizing concurrent communication in the OFDMA backscatter system is proposed. We present a series of mechanisms to deal with the fundamental change of assumptions brought by the new paradigm. First, we process signals at the receiver in a finer granularity for signal classification. Then we remove phase offsets in real time without interrupting the communication. Finally, we propose an extended MUSIC algorithm to improve accuracy with limited localization information in OFDMA backscatter mechanism. We implement a prototype under the 802.11g framework in WARP, based on which we conduct comprehensive experiments to evaluate our propose mechanism. Results show that our system can localize 48 tags simultaneously, while achieving average localization errors within 0.49m. The tag's power consumption is about 55-81.3μW.

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Cited By

Jiang JWang JChen YTong SXie PLiu YLiu YOkoshi TKo JLiKamWa R(2024)Willow: Practical WiFi Backscatter Localization with Parallel TagsProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661853(265-277)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661853
Xu XHuang TKuai XLiang Y(2024)Joint Localization and Signal Detection for Ambient Backscatter Communication SystemsIEEE Transactions on Wireless Communications10.1109/TWC.2024.341411923:10(14437-14451)Online publication date: Oct-2024
https://doi.org/10.1109/TWC.2024.3414119
Tong XGe WTian YLiu ZLiu XQu W(2024) NNE-Tracking: A Neural Network Enhanced Framework for Device-Free Wi-Fi Tracking IEEE Transactions on Mobile Computing10.1109/TMC.2024.335756923:9(8981-8998)Online publication date: Sep-2024
https://doi.org/10.1109/TMC.2024.3357569
Show More Cited By

Index Terms

Batch Localization Based on OFDMA Backscatter
1. Networks
  1. Network services
    1. Location based services

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 3, Issue 1

March 2019

786 pages

EISSN:2474-9567

DOI:10.1145/3323054

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Copyright © 2019 ACM.

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Publication History

Published: 29 March 2019

Accepted: 01 January 2019

Revised: 01 November 2018

Received: 01 May 2018

Published in IMWUT Volume 3, Issue 1

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Cited By

Jiang JWang JChen YTong SXie PLiu YLiu YOkoshi TKo JLiKamWa R(2024)Willow: Practical WiFi Backscatter Localization with Parallel TagsProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661853(265-277)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661853
Xu XHuang TKuai XLiang Y(2024)Joint Localization and Signal Detection for Ambient Backscatter Communication SystemsIEEE Transactions on Wireless Communications10.1109/TWC.2024.341411923:10(14437-14451)Online publication date: Oct-2024
https://doi.org/10.1109/TWC.2024.3414119
Tong XGe WTian YLiu ZLiu XQu W(2024) NNE-Tracking: A Neural Network Enhanced Framework for Device-Free Wi-Fi Tracking IEEE Transactions on Mobile Computing10.1109/TMC.2024.335756923:9(8981-8998)Online publication date: Sep-2024
https://doi.org/10.1109/TMC.2024.3357569
Guo DGu CJiang LLuo WTan R(2022)ILLOCProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35172456:1(1-26)Online publication date: 29-Mar-2022
https://dl.acm.org/doi/10.1145/3517245
Toro UElHalawany BWong AWang LWu K(2022)Backscatter communication-based wireless sensing (BBWS)Journal of Network and Computer Applications10.1016/j.jnca.2022.103518208:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.jnca.2022.103518
Uchiyama ASaruwatari SMaekawa TOhara KHigashino T(2021)Context Recognition by Wireless Sensing: A Comprehensive SurveyJournal of Information Processing10.2197/ipsjjip.29.4629(46-57)Online publication date: 2021
https://doi.org/10.2197/ipsjjip.29.46
Soltanaghaei EDongare APrabhakara AKumar SRowe AWhitehouse K(2021)TagFiProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34480825:1(1-29)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1145/3448082
Soltanaghaei EPrabhakara ABalanuta AAnderson MRabaey JKumar SRowe A(2021)MillimetroProceedings of the 27th Annual International Conference on Mobile Computing and Networking10.1145/3447993.3448627(69-82)Online publication date: 25-Oct-2021
https://dl.acm.org/doi/10.1145/3447993.3448627
Tong XLi HTian XWang X(2021)Wi-Fi Localization Enabling Self-CalibrationIEEE/ACM Transactions on Networking10.1109/TNET.2021.305199829:2(904-917)Online publication date: Apr-2021
https://doi.org/10.1109/TNET.2021.3051998
Tong XWang HLiu XQu W(2021)MapFi: Autonomous Mapping of Wi-Fi Infrastructure for Indoor LocalizationIEEE Transactions on Mobile Computing10.1109/TMC.2021.3108155(1-1)Online publication date: 2021
https://doi.org/10.1109/TMC.2021.3108155
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