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Talks and Poster Presentations (with Proceedings-Entry):

T. Blazek, E. Zöchmann, C. Mecklenbräuker:
"Model Order Selection for LASSO Fitted Millimeter Wave Vehicular Channel Data";
Talk: 2018 IEEE 29th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Bologna; 09-09-2018 - 09-12-2018; in: "2018 IEEE 29th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)", IEEE, (2018), ISBN: 978-1-5386-6009-6; 5 pages.



English abstract:
For analysis of vehicle-to-vehicle (V2V) communications,
a firm understanding of the underlying channel
is crucial. Through spatial filtering of narrow beams
millimeter wave (mmWave) channels become sparse. As
accurate channel models are required, without overfitting
channel measurements, we investigate the optimal model
order given V2V mmWave channel measurements. We
use the complex Least Absolute Shrinkage and Selection
Operator (LASSO) to find a sparse tapped-delay line representation
of the measured channel, and apply the Akaike
Information Criterion to find the optimal model order.
Beyond this optimal order we start to fit measurement
noise. Our results show, that for the given measurements,
4 to 8 taps prove to be an ideal model order.

German abstract:
For analysis of vehicle-to-vehicle (V2V) communications,
a firm understanding of the underlying channel
is crucial. Through spatial filtering of narrow beams
millimeter wave (mmWave) channels become sparse. As
accurate channel models are required, without overfitting
channel measurements, we investigate the optimal model
order given V2V mmWave channel measurements. We
use the complex Least Absolute Shrinkage and Selection
Operator (LASSO) to find a sparse tapped-delay line representation
of the measured channel, and apply the Akaike
Information Criterion to find the optimal model order.
Beyond this optimal order we start to fit measurement
noise. Our results show, that for the given measurements,
4 to 8 taps prove to be an ideal model order.

Keywords:
mmWave, Vehicular Channel Models, cLASSO


Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_271471.pdf


Created from the Publication Database of the Vienna University of Technology.