Compressive sensing with weighted coefficient approach for indoor source localization

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages243-246
Number of pages4
Volume2017-January
ISBN (Electronic)9781509039821
DOIs
Publication statusPublished - Oct 19 2017
Event40th International Conference on Telecommunications and Signal Processing, TSP 2017 - Barcelona, Spain
Duration: Jul 5 2017Jul 7 2017

Other

Other40th International Conference on Telecommunications and Signal Processing, TSP 2017
Country/TerritorySpain
CityBarcelona
Period7/5/177/7/17

Keywords

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

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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