Title :
Localization performance analysis of KNN in IEEE 802.11 TGn channel
Author_Institution :
Dongguk Univ. - Seoul, Seoul, South Korea
Abstract :
With growing demand for location based services, research on high resolution location estimation methods in indoor wireless environments have grown over the years. Currently the most popular localization method based on RSS is the fingerprinting KNN method proposed by Bahl and Padmanabhan due to its simplicity. In this paper we present the experimental results on the multiple antenna KNN method in IEEE 802.11 TGn MIMO channel models for high resolution location estimation.
Keywords :
MIMO communication; antenna arrays; learning (artificial intelligence); pattern classification; telecommunication computing; wireless channels; IEEE 802.11 TGn MIMO channel model; RSS; fingerprinting KNN method; high resolution location estimation method; indoor wireless environment; localization performance analysis; location based service; multiple antenna K-nearest neighbor method; multiple antenna KNN method; Channel models; Fingerprint recognition; IEEE 802.11 Standards; Receiving antennas; Signal to noise ratio; Wireless communication; IEEE 802.11 TGn Model; Localization; Positioning;
Conference_Titel :
ICT Convergence (ICTC), 2011 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4577-1267-8
DOI :
10.1109/ICTC.2011.6082583
