@inproceedings{074dc89da6a844b9a32b34f931950c9c,
title = "Beacon-based proximity detection using compressive sensing for sparse deployment",
abstract = "A proximity-based service (PBS) leverages the estimated proximity to provide users the accessibility to object or location restricted service. This paper exploits the interaction between Bluetooth Low Energy (BLE) Beacon and smartphone to set forth the fundamental building block of a beacon-based PBS system. In real-world scenarios, a beacon-based PBS system might suffer from sparse conditions when some beacons malfunction or beacons can only be deployed in a few specific positions. Motivated by such limitations, a similarity filter extended with compressive sampling matching pursuit (SF-CoSaMP) is proposed to ensure the reliability of proximity detection under such sparse conditions before smartphone proceed to retrieve the corresponding PBS. An extensive simulation with large volume of collected data has been conducted and the results prove the reliability of the proposed algorithm with high detection accuracy in an environment with sparse deployment.",
author = "Ng, \{Pai Chet\} and Li Zhu and James She and Rong Ran and Soochang Park",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 18th IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks, WoWMoM 2017 ; Conference date: 12-06-2017 Through 15-06-2017",
year = "2017",
month = jul,
day = "10",
doi = "10.1109/WoWMoM.2017.7974317",
language = "English",
series = "18th IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks, WoWMoM 2017 - Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "18th IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks, WoWMoM 2017 - Conference",
address = "United States",
}