Enhancing WLAN-based Indoor Localization with Channel State Information

PhD Thesis Proposal Defence


Title: "Enhancing WLAN-based Indoor Localization with Channel State 
        Information"

By

Miss Jiang XIAo


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 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 paper, 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 two systems FILA and FIFS. 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. Afterwards, we exploit the possibilities of 
employing CSI for device-free application scenario, 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.


Date:			Friday, 7 March 2014

Time:			2:00pm - 4:00pm

Venue:			Room 5501
 			Lifts 25-26

Committee Members:	Prof. Bo Li (Chairperson)
 			Prof. Lionel M Ni (Supervisor)
			Prof. Shing-Chi Cheung
                        Dr. Qiong Luo
 			

**** ALL are Welcome ****