Direct Localization for Massive MIMO

Large-scale MIMO systems are well known for their advantages in communications, but they also have the potential for providing very accurate localization, thanks to their high angular resolution. A difficult problem arising indoors and outdoors is localizing users over multipath channels. Localizati...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2017-05, Vol.65 (10), p.2475-2487
Main Authors: Garcia, Nil, Wymeersch, Henk, Larsson, Erik G., Haimovich, Alexander M., Coulon, Martial
Format: Article
Language:English
Subjects:
5G mobile communication
Antenna accessories
Antenna arrays
Array signal processing
Base stations
compressed sensing
Computer Science
direction-of-arrival estimation
Estimation
MIMO
multipath channels
navigation
parameter estimation
Position measurement
Signal and Image Processing
signal processing algorithms
sparse matrices
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Summary:Large-scale MIMO systems are well known for their advantages in communications, but they also have the potential for providing very accurate localization, thanks to their high angular resolution. A difficult problem arising indoors and outdoors is localizing users over multipath channels. Localization based on angle of arrival (AOA) generally involves a two-step procedure, where signals are first processed to obtain a user's AOA at different base stations, followed by triangulation to determine the user's position. In the presence of multipath, the performance of these methods is greatly degraded due to the inability to correctly detect and/or estimate the AOA of the line-of-sight (LOS) paths. To counter the limitations of this two-step procedure which is inherently suboptimal, we propose a direct localization approach in which the position of a user is localized by jointly processing the observations obtained at distributed massive MIMO base stations. Our approach is based on a novel compressed sensing framework that exploits channel properties to distinguish LOS from non-LOS signal paths, and leads to improved performance results compared to previous existing methods.
ISSN:1053-587X
1941-0476
1941-0476
DOI:10.1109/TSP.2017.2666779