Direct localization for massive MIMO

Nil Garcia, Henk Wymeersch, Erik G. Larsson, Alexander M. Haimovich, Martial Coulon

Research output: Contribution to journalArticlepeer-review

131 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number7849233
Pages (from-to)2475-2487
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume65
Issue number10
DOIs
StatePublished - May 15 2017

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • 5G mobile communication
  • MIMO
  • antenna arrays
  • base stations
  • compressed sensing
  • direction-of-arrival estimation
  • multipath channels
  • navigation
  • parameter estimation
  • position measurement
  • signal processing algorithms
  • sparse matrices

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