Fingerprint-based location positoning using improved KNN

Author

Xiaomei Liang ; XueRong Gou ; Yong Liu

Author_Institution

Network & Educ. Inst., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2012

fDate

21-23 Sept. 2012

Firstpage

57

Lastpage

61

Abstract

Location estimation has become one of the most popular research areas for the wide application of Location Based Services (LBS). K nearest neighbors (KNN) algorithm is commonly used in fingerprinting approach, and it has been widely used for decades due to its simplicity and effectiveness. However, the main drawback of KNN algorithm is obvious. Theoretical behavior can hardly be obtained because KNN is sensitive to the value of K and it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous irrelevant features. In order to fill this gap, an improved KNN algorithm is introduced. And this algorithm is beneficial to location estimation in a real GSM network.

Keywords

cellular radio; pattern classification; radionavigation; telecommunication computing; GSM network; LBS; fingerprint-based location positoning approach; improved KNN algorithm; k-nearest neighbors algorithm; location based services; location estimation; Accuracy; Adaptation models; Euclidean distance; Fingerprint recognition; GSM; Mobile communication; Distance weights; Featured weights; Fingerprint; K nearest neighbors (KNN); Location estimation; Log-Distance Path Loss (LDPL) model;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Infrastructure and Digital Content (IC-NIDC), 2012 3rd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4673-2201-0

Type

conf

DOI

10.1109/ICNIDC.2012.6418711

Filename

6418711