THESIS
2014
xiii, 115 pages : illustrations ; 30 cm
Abstract
With marvelous development of wireless techniques and ubiquitous deployment of
wireless systems indoors, myriads of Indoor Location-Based Services (ILBS) have permeated
into numerous aspects of modern life. The most fundamental functionality, is
to pinpoint the location of the target via wireless devices. According to different application
scenarios, we can classify the existing indoor positioning techniques into two
categories: device-based and device-free. In general, the applications that requiring specific
devices on the entities to fulfill the localization function belong to the device-based
category. Otherwise, the ones whose subjects carry no device pertain to device-free.
WLAN has been witnessed to be a promising technique for indoor localization owing
to its wide avail...[
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With marvelous development of wireless techniques and ubiquitous deployment of
wireless systems indoors, myriads of Indoor Location-Based Services (ILBS) have permeated
into numerous aspects of modern life. The most fundamental functionality, is
to pinpoint the location of the target via wireless devices. According to different application
scenarios, we can classify the existing indoor positioning techniques into two
categories: device-based and device-free. In general, the applications that requiring specific
devices on the entities to fulfill the localization function belong to the device-based
category. Otherwise, the ones whose subjects carry no device pertain to device-free.
WLAN has been witnessed to be a promising technique for indoor localization owing
to its wide availability and prevalent infrastructure. Most WLAN-based positioning
systems depend on received signal strength (RSS). However, RSS value is not reliable
due to its coarse measurement and high temporal variability. In this thesis, we first
propose a new alternative called channel state information (CSI) which processes beneficial
properties for accurate localization, including: frequency diversity and temporal
stability. We then leverage CSI for device-based positioning and design three systems
FILA , FIFS and NomLoc. FILA applies ranging approach to effectively compensate the multipath effects in complicated indoor environments. FIFS is a fingerprinting system
that explores CSI to manifest a unique location. The NomLoc system leverages
the mobility of nomadic APs and fine-grained CSI to dynamically adjust the WLAN
network topology without calibration efforts. Afterwards, we exploit the possibilities
of employing CSI for device-free application scenarios, and design an indoor motion
detection system FIMD, which is an essential primitive for localization. We continue to
further realize a device-free fingerprinting system Pilot based on the observation that
CSI is capable of distinguishing the environment variances when the object presents
in different positions. We conduct experiments in several typical indoor scenarios with
commercial IEEE 802.11 NICs. Extensive experiments demonstrate that CSI is superior
to RSS for WLAN-based indoor localization in both device-based and device-free
circumstances, and the performance gain can be over 75 percents.
keywords: Wireless Network, PHY Layer, CSI, RSS, Nomadic APs
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