CSI-Based Probabilistic Indoor Position Determination: An Entropy Solution - Archive ouverte HAL Access content directly
Journal Articles IEEE Access Year : 2019

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.
Fichier principal
Vignette du fichier
08911385.pdf (2.03 Mo) Télécharger le fichier
Origin Publisher files allowed on an open archive
Loading...

Dates and versions

hal-02444914 , version 1 (20-01-2020)

Licence

Identifiers

Cite

Luan Chen, Iness Ahriz, Didier Le Ruyet. CSI-Based Probabilistic Indoor Position Determination: An Entropy Solution. IEEE Access, 2019, 7, pp.170048-170061. ⟨10.1109/ACCESS.2019.2955747⟩. ⟨hal-02444914⟩
97 View
307 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More