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Tracking time-variant cluster parameters in MIMO channel measurements: algorithm and results

Czink, Nicolai ; Tian, Ruiyuan LU ; Wyne, Shurjeel LU ; Eriksson, Gunnar LU ; Tufvesson, Fredrik LU ; Zemen, Thomas ; Nuutinen, Jukka-Pekka ; Ylitalo, Juha ; Bonek, Ernst and Molisch, Andreas LU (2007) 3rd COST2100 Management Committee Meeting, 2007
Abstract
This paper presents a joint clustering-and-tracking framework to identify time-variant cluster parameters
for geometry-based stochastic MIMO channel models.
The method uses a Kalman filter for tracking and predicting cluster positions, a novel consistent
initial guess procedure that accounts for predicted cluster centroids, and the well-known KPower-
Means algorithm for cluster identification.
We tested the framework by applying it to three entirely different sets of MIMO channel measurement
data obtained by different channel sounders: indoor measurements conducted at 2.55
GHz, outdoor rural measurements at 300 MHz, and outdoor sub-urban measurements at 2.0 GHz.
The time-variant cluster parameters of... (More)
This paper presents a joint clustering-and-tracking framework to identify time-variant cluster parameters
for geometry-based stochastic MIMO channel models.
The method uses a Kalman filter for tracking and predicting cluster positions, a novel consistent
initial guess procedure that accounts for predicted cluster centroids, and the well-known KPower-
Means algorithm for cluster identification.
We tested the framework by applying it to three entirely different sets of MIMO channel measurement
data obtained by different channel sounders: indoor measurements conducted at 2.55
GHz, outdoor rural measurements at 300 MHz, and outdoor sub-urban measurements at 2.0 GHz.
The time-variant cluster parameters of interest are: (i) cluster movement, (ii) change of cluster
spreads, (iii) cluster lifetimes, and birth and death rates of cluster.
We find that clusters show significant movement in parameter space depending on the environment.
The spreads of individual clusters change rather randomly over their lifetime, with a
standard deviation up to 150% of their mean spread. The cluster lifetime is approximately exponentially
distributed, however additionally one has to account for long-living clusters coming from
the line-of-sight path or from major reflectors. (Less)
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Contribution to conference
publication status
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conference name
3rd COST2100 Management Committee Meeting, 2007
conference location
Duisburg, Germany
conference dates
2007-09-10 - 2007-09-12
language
English
LU publication?
yes
id
e332dfc3-760a-4fd7-ad44-c4b6b4bdf314 (old id 961399)
date added to LUP
2016-04-04 14:22:39
date last changed
2021-06-17 08:23:28
@misc{e332dfc3-760a-4fd7-ad44-c4b6b4bdf314,
  abstract     = {This paper presents a joint clustering-and-tracking framework to identify time-variant cluster parameters<br/>for geometry-based stochastic MIMO channel models.<br/>The method uses a Kalman filter for tracking and predicting cluster positions, a novel consistent<br/>initial guess procedure that accounts for predicted cluster centroids, and the well-known KPower-<br/>Means algorithm for cluster identification.<br/>We tested the framework by applying it to three entirely different sets of MIMO channel measurement<br/>data obtained by different channel sounders: indoor measurements conducted at 2.55<br/>GHz, outdoor rural measurements at 300 MHz, and outdoor sub-urban measurements at 2.0 GHz.<br/>The time-variant cluster parameters of interest are: (i) cluster movement, (ii) change of cluster<br/>spreads, (iii) cluster lifetimes, and birth and death rates of cluster.<br/>We find that clusters show significant movement in parameter space depending on the environment.<br/>The spreads of individual clusters change rather randomly over their lifetime, with a<br/>standard deviation up to 150% of their mean spread. The cluster lifetime is approximately exponentially<br/>distributed, however additionally one has to account for long-living clusters coming from<br/>the line-of-sight path or from major reflectors.},
  author       = {Czink, Nicolai and Tian, Ruiyuan and Wyne, Shurjeel and Eriksson, Gunnar and Tufvesson, Fredrik and Zemen, Thomas and Nuutinen, Jukka-Pekka and Ylitalo, Juha and Bonek, Ernst and Molisch, Andreas},
  language     = {eng},
  title        = {Tracking time-variant cluster parameters in MIMO channel measurements: algorithm and results},
  year         = {2007},
}