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...[ Read more ]

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