Statistical Trilateration With Skew-t Distributed Errors in LTE Networks

Philipp Müller, José A. Del Peral-Rosado, Robert Piché, Gonzalo Seco-Granados

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

© 2016 IEEE. Localization accuracy of trilateration methods in long term evolution (LTE) cellular networks, which are based on time-of-arrival, may be highly degraded due to multipath and non-line of sight conditions in urban and indoor environments. Multipath mitigation techniques usually involve a high computational burden and require wideband signals to be effective, which limit their adoption in certain low-cost and low-power mobile applications using narrow-band signals. As an alternative to these conventional techniques, this paper analyzes an expectation maximization (EM) localization algorithm that considers the skewness introduced by multipath in the LTE ranging error distribution. The EM algorithm is extensively studied with realistic emulated LTE signals of 1.4-MHz bandwidth. The EM method is compared with a standard nonlinear least squares (NLS) algorithm under ideal simulated conditions and using realistic outdoor measurements from a laboratory testbed. The EM method outperforms the NLS method when the ranging errors in the training and test stages have similar distributions.
Original languageEnglish
Article number7530886
Pages (from-to)7114-7127
JournalIEEE Transactions on Wireless Communications
Volume15
Issue number10
DOIs
Publication statusPublished - 1 Oct 2016

Keywords

  • expectation maximization algorithm
  • localization
  • LTE
  • skew-t distribution
  • Statistical trilateration

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