@inproceedings{962ae39d192645e1a11ffa7db16cca3c,
title = "Compressive sensing with weighted coefficient approach for indoor source localization",
abstract = "In this work, indoor sensor localization is investigated based on the received-signal-strength-indicator (RSSI) using the compressive sensing (CS) framework. The fingerprints of several ZigBee base-stations are used to construct the dictionary matrix. We propose a weighted-coefficient-approach (WCA) to determine the sensor position based on the solution of the CS problem. Numerical simulations and experiments are conducted to show that the proposed WCA outperforms the conventional CS-based approach for source localization. Numerical results demonstrate that the WCA can be used to determine the sensor position with high accuracy.",
keywords = "Compressive sensing (CS), Indoor source localization, Map-based, RSSI",
author = "Rana Ramadan and Arwa Jwaifel and Hanan Al-Tous and Imad Barhumi",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 40th International Conference on Telecommunications and Signal Processing, TSP 2017 ; Conference date: 05-07-2017 Through 07-07-2017",
year = "2017",
month = oct,
day = "19",
doi = "10.1109/TSP.2017.8075978",
language = "English",
series = "2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "243--246",
editor = "Norbert Herencsar",
booktitle = "2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017",
}