Contributions to Proceedings:

M. Gan, Z. Xu, C. Mecklenbräuker, T. Zemen:
"Cluster Lifetime Characterization for Vehicular Communication Channels";
in: "2015 9th European Conference on Antennas and Propagation", IEEE Xplore, 2015, 1 - 5.

English abstract:
Simulating the time-variance of vehicular channels correctly remains a challenging topic.
We are interested in parsimonious mathematical channel models, in which only significant groups of multipath components (MPCs) are included.
The MPCs are grouped in the delay-Doppler domain, which enables the development of cluster-based channel models.
However, the characterization of time-variant vehicular channel parameters based on a joint clustering-and-tracking framework
has not been adequately studied previously.
In this paper, we focus on the cluster lifetime characterization for vehicular communication channels.
A joint cluster identification-and-tracking approach based on the local scattering function (LSF) is applied, which takes the delay and Doppler domains into consideration.

The proposed approach uses a density-based spatial clustering of applications with noise (DBSCAN) algorithm for identification.
The cluster centroid tracking is based on the multipath component distance (MCD) matrix.
We apply this approach to real-world vehicular channel measurements.
The time-varying cluster lifetimes are tracked according via the cluster centroids for two different scenarios.
The results indicate that the detected cluster which is related to the line-of-sight (LOS) component persists throughout the measurement run and
contributes the highest gain level for both scenarios.
The clusters detected from the traffic signs and large moving vehicles also persist for a longer period, whereas many clusters associated with discrete scatters along the roadside appear for very short periods.

Channel measurements, MIMO, vehicular, nonstationary, Doppler, geometrical model, statistical model

Electronic version of the publication:

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