Open Access

Statistical Analysis of Multipath Clustering in an Indoor Office Environment

  • Emmeric Tanghe1Email author,
  • Wout Joseph1, 2,
  • Martine Liénard2,
  • Abdelmottaleb Nasr2,
  • Paul Stefanut2,
  • Luc Martens1 and
  • Pierre Degauque2
EURASIP Journal on Wireless Communications and Networking20112011:263134

https://doi.org/10.1155/2011/263134

Received: 12 August 2010

Accepted: 21 February 2011

Published: 14 March 2011

Abstract

A parametric directional-based MIMO channel model is presented which takes multipath clustering into account. The directional propagation path parameters include azimuth of arrival (AoA), azimuth of departure (AoD), delay, and power. MIMO measurements are carried out in an indoor office environment using the virtual antenna array method with a vector network analyzer. Propagation paths are extracted using a joint 5D ESPRIT algorithm and are automatically clustered with the K-power-means algorithm. This work focuses on the statistical treatment of the propagation parameters within individual clusters (intracluster statistics) and the change in these parameters from one cluster to another (intercluster statistics). Motivated choices for the statistical distributions of the intracluster and intercluster parameters are made. To validate these choices, the parameters' goodness of fit to the proposed distributions is verified using a number of powerful statistical hypothesis tests. Additionally, parameter correlations are calculated and tested for their significance. Building on the concept of multipath clusters, this paper also provides a new notation of the MIMO channel matrix (named FActorization into a BLock-diagonal Expression or FABLE) which more visibly shows the clustered nature of propagation paths.

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Authors’ Affiliations

(1)
Department of Information Technology, Ghent University-IBBT
(2)
Group TELICE, IEMN, University of Lille

Copyright

© Emmeric Tanghe et al. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.