Citation

Tan, Ai Hui (2024) A New Distance Metric Based on Bias-Variance Tradeoff for Wireless Fingerprinting. IEEE Transactions on Instrumentation and Measurement, 73. pp. 1-10. ISSN 0018-9456

Text A_New_Distance_Metric_Based_on_Bias-Variance_Tradeoff_for_Wireless_Fingerprinting.pdf - Published Version Restricted to Repository staff only Download (10MB)

Abstract

— This article proposes a new distance metric for indoor positioning based on wireless fingerprinting, referred to as the weighted bias-variance (WBV) metric. The WBV metric is parameterized by a single parameter that is adjusted based on the concept of bias-variance tradeoff, making it highly effective in scenarios where there is a network reconfiguration or change in the environmental layout. The optimal setting was found to be minimally affected by the number of nearest neighbors in the estimation algorithm as well as the access point (AP) selection schemes. In an experiment at a university library, the switch from the Manhattan metric to the WBV metric after a network reconfiguration achieved a reduction in the mean position error (MPE), standard deviation and median of the error distribution of 34.9%, 22.1%, and 41.5%, respectively, with negligible changes to the floor accuracy (FA). When the number of APs was reduced, the corresponding reduction was 42.7%, 35.5%, and 46.3%, respectively. In another experiment at a university faculty building, the switch from the Manhattan metric to the WBV metric after a layout change attained a reduction in the MPE, standard deviation, and median of the error distribution of 55.1%, 62.6%, and 23.1%, respectively. The FA improved by 22.2%. The drastic improvement in accuracy has the potential to significantly advance indoor positioning for the ubiquitous Internet of Things

Item Type:	Article
Uncontrolled Keywords:	Fingerprinting
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare. Criminology > HV6001-7220.5 Criminology > HV6035-6197 Criminal anthropology Including criminal types, criminal psychology, prison psychology, causes of crime
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Nov 2024 00:34
Last Modified:	04 Nov 2024 00:34
URII:	http://shdl.mmu.edu.my/id/eprint/13063

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