Direct Localization for Massive MIMO
Artikel i vetenskaplig tidskrift, 2017
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.
Array signal processing
parameter estimation
multipath channels
Antenna arrays
Position measurement
5G mobile communication
MIMO
navigation
position measurement
Antenna accessories
Base stations
compressed sensing
signal processing algorithms
sparse matrices
Estimation
direction-of-arrival estimation
antenna arrays
MIMO
base stations
Författare
Nil Garcia
Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner
Henk Wymeersch
Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner
E. G. Larsson
Linkopings universitet
Alexander M. Haimovich
New Jersey Institute of Technology
Martial Coulon
Universite de Toulouse
IEEE Transactions on Signal Processing
1053-587X (ISSN)
Vol. 65 10 2475-2487 7849233Coopnet
Europeiska kommissionen (FP7) (EC/FP7/258418), 2011-05-01 -- 2016-04-30.
Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier (SSIF 2011)
Signalbehandling
DOI
10.1109/TSP.2017.2666779