Visible light communications-based indoor positioning via compressed sensing

Kristina Gligoric, Manisha Ajmani, Dejan Vukobratovic, Sinan Sinanovic

    Research output: Contribution to journalArticlepeer-review

    33 Citations (Scopus)
    258 Downloads (Pure)


    This letter presents an approach for visible light communication-based indoor positioning using compressed sensing. We consider a large number of light emitting diodes (LEDs) simultaneously transmitting their positional information and a user device equipped with a photo diode. By casting the LED signal separation problem into an equivalent compressed sensing framework, the user device is able to detect the set of nearby LEDs using sparse signal recovery algorithms. From this set and using proximity method, position estimation is proposed based on the concept that if signal separation is possible, then the overlapping light beam regions lead to decrease in positioning error due to increase in the number of reference points. The proposed method is evaluated in a LED-illuminated large-scale indoor open-plan office space scenario. The positioning accuracy is compared against the positioning error lower bound of the proximity method, for various system parameters.
    Original languageEnglish
    Pages (from-to)1410-1413
    Number of pages4
    JournalIEEE Communications Letters
    Issue number7
    Early online date7 May 2018
    Publication statusPublished - Jul 2018


    • visible light
    • indoor positioning system
    • visible light communication
    • sparse reconstruction
    • channel gain
    • compressed sensing
    • Indoor positioning system

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Computer Science Applications
    • Modelling and Simulation


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