Packet Delivery Ratio Fingerprinting: Toward Device-Invariant Passive Indoor Localization

Duan, Yaoxin; Lam, Kam-Yiu; Lee, Victor C. S.; Nie, Wendi; Li, Hao; Ng, Joseph Kee‐Yin

doi:10.1109/jiot.2019.2963436

Cited by 10 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the data rates at different locations are different, Duan et al [19] exploits data rate information of all available APs as the fingerprints for localization. In order to improve the resolution, their subsequent work [7] includes other fingerprints such as packet delivery ratio (PDR) for localization, which improves the average accuracy to 2.5 m.…”

Section: Phone State Decisionmentioning

confidence: 99%

“…This causes device heterogeneity and is the primary challenge of indoor localization [33]. If the WiFi device used in the training phase is different from the actual device used in the testing phase, the localization accuracy could be significantly reduced [7]. To mitigate this problem, one may use special fingerprints such as data rate (DR) [19], RSS ratio [34], RSSI difference [35] to avoid heterogeneity.…”

Section: Device Heterogeneitymentioning

confidence: 99%

“…A phone is inactive when it is not transmitting data frames. Consequently, existing passive indoor localization schemes that uses data rate [19] or packet delivery ratio [7] as fingerprints may not have sufficient data for localization when the phone is inactive. This paper studies passive indoor localization with solutions to the problems listed above for active and inactive phones.…”

Section: Current Literature On Indoor Localizationmentioning

confidence: 99%

“…2(a), after obtaining the MAC address of the target phone from PRF, the AP will send K RTS frames to that MAC address every ∆t. According to the IEEE 802.11 standard, when an AP transmits an RTS frame to a target, the target should immediately reply a CTS frame to the AP even if it is not associated with the AP [7]. Therefore, the phone will be forced to respond with several CTS frames back to the corresponding AP.…”

Section: B Inactive Phone Localizationmentioning

confidence: 99%

“…The active localization scheme, being the mainstream approach, collects WiFi signals from a mobile device to infer the user's positions [5], [6]. It requires a dedicated software to be installed on mobile devices for WiFi scanning and logging [7]. In contrast, passive localization is fully implemented on WiFi access points (APs) and does not require any software to be installed on mobile devices [4], [8].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Passive Indoor Localization with WiFi Fingerprints

Hoang¹,

Yuen²,

Ren³

et al. 2021

Preprint

View full text Add to dashboard Cite

This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the mobile device is not required. To resolve the data insufficiency problem, flow control signals such as request to send (RTS) and clear to send (CTS) are utilized. In our model, received signal strength indicator (RSSI) and channel state information (CSI) are used as fingerprints for several algorithms, including deterministic, probabilistic and neural networks localization algorithms. We further investigated localization algorithms performance through extensive on-site experiments with various models of phones at hundreds of testing locations. We demonstrate that our passive scheme achieves an average localization error of ∼0.8 m when the phone is actively transmitting data frames and ∼1.5 m when it is not transmitting data frames.

show abstract

Section: Phone State Decisionmentioning

confidence: 99%