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.

Antenna accessories

MIMO

5G mobile communication

sparse matrices

position measurement

multipath channels

Estimation

antenna arrays

base stations

Antenna arrays

direction-of-arrival estimation

MIMO

navigation

Array signal processing

signal processing algorithms

Base stations

parameter estimation

Position measurement

compressed sensing

Författare

Nil Garcia

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Forskning Andra publikationer

Henk Wymeersch

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Forskning Andra publikationer

E. G. Larsson

Linköpings universitet

Alexander M. Haimovich

New Jersey Institute of Technology

Martial Coulon

Université de Toulouse

IEEE Transactions on Signal Processing

1053-587X (ISSN)

Vol. 65 10 2475-2487 7849233

Coopnet

Europeiska kommissionen (FP7), 2011-05-01 -- 2016-04-30.

Visa projekt

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Signalbehandling

DOI

10.1109/TSP.2017.2666779

Publikationsdata kopplat till DOI

Mer information

Senast uppdaterat

2018-07-04

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