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WidthSense: Wi-Fi Discovery via Distance-Based Correlation Analysis

Authors
Choi, Jaehyuk
Issue Date
Feb-2017
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Wi-Fi discovery; frequency domain analysis; euclidean distance; algorithms
Citation
IEEE COMMUNICATIONS LETTERS, v.21, no.2, pp.422 - 425
Journal Title
IEEE COMMUNICATIONS LETTERS
Volume
21
Number
2
Start Page
422
End Page
425
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6459
DOI
10.1109/LCOMM.2016.2626435
ISSN
1089-7798
Abstract
In this letter, we present a lightweight yet accurate scheme for mobile devices, called WidthSense, that identifies available Wi-Fi systems by using a collocated heterogeneous wireless personal area network (WPAN) radio such as Bluetooth or ZigBee. Motivated by the observation that Wi-Fi signals in a 2.4 GHz ISM band can be sensed by a WPAN radio over the frequency range of the corresponding Wi-Fi channel, WidthSense exploits the temporally correlated fluctuations in multiple narrowband WPAN-channels. To this end, we employ a distance-based similarity as a measurement of dependence between WPAN channels. We implement a prototype of WidthSense using a Bluetooth-compliant wireless transceiver, and demonstrate its efficiency. Experimental results show that WidthSense achieves high detection accuracy with a short delay (-500 ms).
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Choi, Jaehyuk
College of IT Convergence (Department of Software)
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