Title page for ETD etd-06282011-154448


Type of Document Master's Thesis
Author Mendoza, Hermie P
URN etd-06282011-154448
Title Distributed Localization for Wireless Distributed Networks in Indoor Environments
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Reed, Jeffrey Hugh Committee Chair
Bose, Tamal Committee Member
Volos, Haris I. Committee Member
Keywords
  • fingerprinting
  • indoor localization
  • wireless distributed computing networks
  • localization
Date of Defense 2011-06-28
Availability unrestricted
Abstract
Positioning systems enable location-awareness for mobile devices, computers, and even tactical

radios. From the collected location information, location-based services can be realized.

One type of positioning system is based on location fingerprints. Unlike the conventional

positioning techniques of time of or time delay of arrival (TOA/TDOA) or even angle of arrival

(AOA), fingerprinting associates unique characteristics such as received signal strength

(RSS) that differentiates a location from another location. The location-dependent characteristics

then can be used to infer a user’s location. Furthermore, fingerprinting requires no

specialized hardware because of its reliance on an existing communications infrastructure.

In estimating a user’s position, fingerprint-based positioning systems are centrally calculated

on a mobile computer using either a Euclidean distance algorithm, Bayesian statistics, or

neural networks. With large service areas and, subsequently, large radio maps, one mobile

computer may not have the adequate resources to locally compute a user’s position. Wireless

distributed computing provides a means for the mobile computer to meet the location-based

service requirements and increase its network lifetime. This thesis develops distributed localization

algorithms to be used in an indoor fingerprint-based positioning system. Fingerprint

calculations are not computed on a single device, but rather on a wireless distributed computing

network on Virginia Tech’s Cognitive Radio Network Testbed (CORNET).

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