Precise power delay profiling with commodity Wi-Fi
Power 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 d...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/151316 |
| _version_ | 1811694021478711296 |
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| author | Xie, Yaxiong Li, Zhenjiang Li, Mo |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Xie, Yaxiong Li, Zhenjiang Li, Mo |
| author_sort | Xie, Yaxiong |
| collection | NTU |
| description | Power 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. |
| first_indexed | 2024-10-01T07:00:57Z |
| format | Journal Article |
| id | ntu-10356/151316 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:00:57Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1513162021-06-16T03:07:47Z Precise power delay profiling with commodity Wi-Fi Xie, Yaxiong Li, Zhenjiang Li, Mo School of Computer Science and Engineering Engineering::Computer science and engineering Wireless Communication Channel State Information Power 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. Ministry of Education (MOE) Nanyang Technological University This 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). 2021-06-16T03:07:47Z 2021-06-16T03:07:47Z 2018 Journal Article Xie, 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.2018.2860991 1536-1233 0000-0003-4258-6655 0000-0002-3296-3392 0000-0002-6047-9709 https://hdl.handle.net/10356/151316 10.1109/TMC.2018.2860991 2-s2.0-85050725900 6 18 1342 1355 en RG125/17 MOE2016-T2-2-023 M4081879 IEEE Transactions on Mobile Computing © 2018 IEEE. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Wireless Communication Channel State Information Xie, Yaxiong Li, Zhenjiang Li, Mo Precise power delay profiling with commodity Wi-Fi |
| title | Precise power delay profiling with commodity Wi-Fi |
| title_full | Precise power delay profiling with commodity Wi-Fi |
| title_fullStr | Precise power delay profiling with commodity Wi-Fi |
| title_full_unstemmed | Precise power delay profiling with commodity Wi-Fi |
| title_short | Precise power delay profiling with commodity Wi-Fi |
| title_sort | precise power delay profiling with commodity wi fi |
| topic | Engineering::Computer science and engineering Wireless Communication Channel State Information |
| url | https://hdl.handle.net/10356/151316 |
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