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).
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - ETC > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6459)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.