Gaussian Process Modeling of Specular Multipath Components

H. A. Nguyen*, M. Rath, E. Leitinger, V. K. Nguyen, K. Witrisal*

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

The consideration of ultra-wideband (UWB) and mm-wave signals allows for a channel description decomposed into specular multipath components (SMCs) and dense/diffuse multipath. In this paper, the amplitude and phase of SMCs are studied. Gaussian Process regression (GPR) is used as a tool to analyze and predict the SMC amplitudes and phases based on a measured training data set. In this regard, the dependency of the amplitude (and phase) on the angle-of-arrival/angle-of-departure of a multipath component is analyzed, which accounts for the incident angle and incident position of the signal at a reflecting surface-and thus for the reflection characteristics of the building material-and for the antenna gain patterns. The GPR model describes the similarities between different data points. Based on its model parameters and the training data, the amplitudes of SMCs are predicted at receiver positions that have not been measured in the experiment. The method can be used to predict a UWB channel impulse response at an arbitrary position in the environment.

Original languageEnglish
Article number5216
JournalSensors
Volume10
Issue number15
DOIs
Publication statusPublished - 1 Jul 2020

Keywords

  • Gaussian process regression
  • Geometric-stochastic channelmodel
  • Multipath radio channels

ASJC Scopus subject areas

  • Engineering(all)
  • Instrumentation
  • Materials Science(all)
  • Fluid Flow and Transfer Processes
  • Process Chemistry and Technology
  • Computer Science Applications

Fields of Expertise

  • Information, Communication & Computing

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