Compressive sensing with weighted coefficient approach for indoor source localization

Rana Ramadan; Arwa Jwaifel; Hanan Al-Tous; Imad Barhumi

doi:10.1109/TSP.2017.8075978

Compressive sensing with weighted coefficient approach for indoor source localization

Rana Ramadan, Arwa Jwaifel, Hanan Al-Tous, Imad Barhumi

Department of Electrical and Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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.

Original language	English
Title of host publication	2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	243-246
Number of pages	4
Volume	2017-January
ISBN (Electronic)	9781509039821
DOIs	https://doi.org/10.1109/TSP.2017.8075978
Publication status	Published - Oct 19 2017
Event	40th International Conference on Telecommunications and Signal Processing, TSP 2017 - Barcelona, Spain Duration: Jul 5 2017 → Jul 7 2017

Other

Other	40th International Conference on Telecommunications and Signal Processing, TSP 2017
Country/Territory	Spain
City	Barcelona
Period	7/5/17 → 7/7/17

Keywords

Compressive sensing (CS)
Indoor source localization
Map-based
RSSI

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing

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10.1109/TSP.2017.8075978

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Ramadan, R., Jwaifel, A., Al-Tous, H., & Barhumi, I. (2017). Compressive sensing with weighted coefficient approach for indoor source localization. In 2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017 (Vol. 2017-January, pp. 243-246). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TSP.2017.8075978

Compressive sensing with weighted coefficient approach for indoor source localization. / Ramadan, Rana; Jwaifel, Arwa; Al-Tous, Hanan et al.

2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 243-246.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ramadan, R, Jwaifel, A, Al-Tous, H & Barhumi, I 2017, Compressive sensing with weighted coefficient approach for indoor source localization. in 2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 243-246, 40th International Conference on Telecommunications and Signal Processing, TSP 2017, Barcelona, Spain, 7/5/17. https://doi.org/10.1109/TSP.2017.8075978

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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.",

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booktitle = "2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017",

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AU - Ramadan, Rana

AU - Jwaifel, Arwa

AU - Al-Tous, Hanan

AU - Barhumi, Imad

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Y1 - 2017/10/19

N2 - 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.

AB - 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.

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KW - Indoor source localization

KW - Map-based

KW - RSSI

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BT - 2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017

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ER -

Compressive sensing with weighted coefficient approach for indoor source localization

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Keywords

ASJC Scopus subject areas

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