TY - JOUR
T1 - Visible light communications-based indoor positioning via compressed sensing
AU - Gligoric, Kristina
AU - Ajmani, Manisha
AU - Vukobratovic, Dejan
AU - Sinanovic, Sinan
N1 - Acceptance email provided below by author
AAM: no embargo
Below is acceptance email:
01-May-2018
Dear Author(s),
I am pleased to inform you that your manuscript "Visible Light Communications Based Indoor Positioning via Compressed Sensing," paper number CL2018-0746, is now accepted for publication in the IEEE Communications Letters. The reviewers' comments are in the later part of the email so please take this opportunity to improve your paper before uploading the final version. After reading the revised paper again, I also agree with one of the comments that the word "novelty" should be excluded from the paper.
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IEEE Communications Letters
PY - 2018/7
Y1 - 2018/7
N2 - 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.
AB - 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.
KW - visible light
KW - indoor positioning system
KW - visible light communication
KW - sparse reconstruction
KW - channel gain
KW - compressed sensing
KW - Indoor positioning system
U2 - 10.1109/LCOMM.2018.2833550
DO - 10.1109/LCOMM.2018.2833550
M3 - Article
SN - 1089-7798
VL - 22
SP - 1410
EP - 1413
JO - IEEE Communications Letters
JF - IEEE Communications Letters
IS - 7
ER -