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Journal articles
CSI-Based Probabilistic Indoor Position Determination: An Entropy Solution
Abstract : Location Fingerprinting (LF) is a promising localization technique that enables enormous commercial and industrial Location-Based Services (LBS). Existing approaches either appeal to the simple Received Signal Strength (RSS), which suffers from dramatic performance degradation due to sophisticated environmental dynamics, or rely on the fine-grained physical layer Channel State Information (CSI), whose intricate structure leads to an increased computational complexity. In this paper, we adopt Autoregres-sive (AR) modeling based entropy of CSI amplitude as location fingerprint, which shares the structural simplicity of RSS while exploiting the most location-specific statistical channel information. On this basis, we design EntLoc, a CSI-based probabilistic indoor localization system using commercial off-the-shelf Wi-Fi devices. EntLoc is deployed in an office building covering over 200 m 2. Extensive indoor scenario experiments corroborate that our proposed system yields superior localization accuracy over previous approaches even with only one signal transmitter.
Cited literature [48 references]
https://hal.archives-ouvertes.fr/hal-02444914
Contributor : Luan Chen <>
Submitted on : Monday, January 20, 2020 - 4:03:18 PM
Last modification on : Tuesday, July 21, 2020 - 9:26:05 AM
Long-term archiving on: : Tuesday, April 21, 2020 - 6:35:56 PM
Contributor : Luan Chen <>
Submitted on : Monday, January 20, 2020 - 4:03:18 PM
Last modification on : Tuesday, July 21, 2020 - 9:26:05 AM
Long-term archiving on: : Tuesday, April 21, 2020 - 6:35:56 PM
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