Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151316
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dc.contributor.authorXie, Yaxiongen_US
dc.contributor.authorLi, Zhenjiangen_US
dc.contributor.authorLi, Moen_US
dc.date.accessioned2021-06-16T03:07:47Z-
dc.date.available2021-06-16T03:07:47Z-
dc.date.issued2018-
dc.identifier.citationXie, Y., Li, Z. & Li, M. (2018). Precise power delay profiling with commodity Wi-Fi. IEEE Transactions On Mobile Computing, 18(6), 1342-1355. https://dx.doi.org/10.1109/TMC.2018.2860991en_US
dc.identifier.issn1536-1233en_US
dc.identifier.other0000-0003-4258-6655-
dc.identifier.other0000-0002-3296-3392-
dc.identifier.other0000-0002-6047-9709-
dc.identifier.urihttps://hdl.handle.net/10356/151316-
dc.description.abstractPower delay profiles characterize multipath channel features, which are widely used in motion-or localization-based applications. The performance of power delay profile obtained using commodity Wi-Fi devices is limited by two dominating factors. The resolution of the derived power delay profile is determined by the channel bandwidth, which is however limited on commodity WiFi. The collected CSI reflects the signal distortions due to both the channel attenuation and the hardware imperfection. A direct derivation of power delay profiles using raw CSI measures, as has been done in the literature, results in significant inaccuracy. In this paper, we present Splicer, a software-based system that derives high-resolution power delay profiles by splicing the CSI measurements from multiple WiFi frequency bands. We propose a set of key techniques to separate the mixed hardware errors from the collected CSI measurements. Splicer adapts its computations within stringent channel coherence time and thus can perform well in the presence of mobility. Our experiments with commodity WiFi NICs show that Splicer substantially improves the accuracy in profiling multipath characteristics, reducing the errors of multipath distance estimation to be less than 2m. Splicer can immediately benefit upper-layer applications. Our case study with recent single-AP localization achieves a median localization error of 0.95m.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.language.isoenen_US
dc.relationRG125/17en_US
dc.relationMOE2016-T2-2-023en_US
dc.relationM4081879en_US
dc.relation.ispartofIEEE Transactions on Mobile Computingen_US
dc.rights© 2018 IEEE. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titlePrecise power delay profiling with commodity Wi-Fien_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.identifier.doi10.1109/TMC.2018.2860991-
dc.identifier.scopus2-s2.0-85050725900-
dc.identifier.issue6en_US
dc.identifier.volume18en_US
dc.identifier.spage1342en_US
dc.identifier.epage1355en_US
dc.subject.keywordsWireless Communicationen_US
dc.subject.keywordsChannel State Informationen_US
dc.description.acknowledgementThis work is supported by Singapore MOE Tier 1 grant RG125/17, Tier 2 grant MOE2016-T2-2-023, and NTU CoE grant M4081879. This work is also partially supported by the ECS grant from the Research Grants Council of Hong Kong (Project No. CityU 21203516), and the GRF grant from the Research Grants Council of Hong Kong (Project No. CityU 11217817).en_US
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