A Time-Variant MIMO Channel Model Directly Parametrised from Measurements

This paper presents the Random-Cluster Model (RCM), a stochastic time-variant, frequency-selective, propagation-based MIMO channel model that is directly parametrised from measurements. Using a fully automated algorithm, multipath clusters are identified from measurement data without user interventi...

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Bibliographic Details
Published inEURASIP journal on wireless communications and networking Vol. 2009; no. 1
Main Authors Czink, Nicolai, Zemen, Thomas, Nuutinen, Jukka-Pekka, Ylitalo, Juha, Bonek, Ernst
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.01.2009
SpringerOpen
Subjects
Advances in Propagation Modeling for Wireless Systems
Communications Engineering
Engineering
Information Systems Applications (incl.Internet)
Networks
Research Article
Signal,Image and Speech Processing
Mutual Information
Reference Channel
Multipath Component
MIMO Channel
Kernel Density Estimator
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Summary:This paper presents the Random-Cluster Model (RCM), a stochastic time-variant, frequency-selective, propagation-based MIMO channel model that is directly parametrised from measurements. Using a fully automated algorithm, multipath clusters are identified from measurement data without user intervention. The cluster parameters are then used to define the propagation environment in the RCM. In this way, the RCM provides a direct link between MIMO channel measurements and MIMO channel modelling. For validation, we take state-of-the-art MIMO measurements, and parametrise the RCM exemplarly. Using three different validation metrics, namely, mutual information, channel diversity, and the novel Environment Characterisation Metric, we find that the RCM is able to reflect the measured environment remarkably well.
ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1155/2009/687238