Cluster-based scatterer identification and characterization in vehicular channels

Laura Bernadó, Anna Roma, Nicolai Czink, Alexander Paier, Thomas Zemen

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review


In this paper, we present a new approach for the identification of scattering objects in the delay and Doppler domain. Until now, the identification was done visually based on the power delay profile and video material recorded in the measurement campaigns. We propose to use automatic methods based on the local scattering function (LSF), which brings the Doppler domain into play. The LSF is a multitaper estimate of the two-dimensional (2D) power spectral density in delay and Doppler. Each peak of the LSF is composed of several multipath components (MPCs) coming from the same scattering object. Our approach consists of two steps: (i) detection of the relevant peaks, and (ii) assignment of MPCs to the scattering objects using a clustering algorithm. We use a modified a modified version of the density-based clustering of applications with noise algorithm, where we use the MPC distance. We apply the method to a set of vehicular radio channel measurements and extract the time-varying cluster parameters. The clusters have ellipsoidal shape with their longer axis in the Doppler domain. The first detected cluster presents different properties than the rest of the clusters, being larger, constant in time, and more static in the delay-Doppler plane. By properly identifying only the relevant scattering objects, vehicular channel models, such as the geometry-based stochastic channel model, can be simplified significantly.
Original languageEnglish
Title of host publication17th European Wireless 2011-Sustainable Wireless Technologies
Number of pages6
Publication statusPublished - 2011
Event17th European Wireless 2011 - Sustainable Wireless Technologies -
Duration: 27 Apr 201129 Apr 2011


Conference17th European Wireless 2011 - Sustainable Wireless Technologies

Research Field

  • Enabling Digital Technologies


Dive into the research topics of 'Cluster-based scatterer identification and characterization in vehicular channels'. Together they form a unique fingerprint.

Cite this