Gedschold J, Schneider C, Kaske M, Thoma RS, Del Galdo G, Boban M, Luo J (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2018-September
Pages Range: 68-72
Conference Proceedings Title: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Event location: Bologna, ITA
ISBN: 9781538660096
DOI: 10.1109/PIMRC.2018.8580979
Reliable and accurate multipath clustering results are essential to design and parameterize geometry based (stochastic) channel models proposed by organizations such as 3GPP, COST, WINNER and others. Clustering within wireless channel models assumes that multipath components a rrive/depart with similar properties in the considered parameter domains. We propose a new approach combining tracking and initialization of the classic K-Means clustering algorithm. The results show a significantly improved consistency for cluster estimation, which subsequently allows for analyzing the lifetime of these clusters. Finally, we apply the proposed approach on two urban macro channel sounding datasets and compare them to the current 3GPP standard. We found that the angular parameters are rather similar to the standard whereas the cluster delay spreads and the number of rays per cluster differ significantly.
APA:
Gedschold, J., Schneider, C., Kaske, M., Thoma, R.S., Del Galdo, G., Boban, M., & Luo, J. (2018). Tracking based Multipath Clustering in Vehicle-to-Infrastructure Channels. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC (pp. 68-72). Bologna, ITA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Gedschold, Jonas, et al. "Tracking based Multipath Clustering in Vehicle-to-Infrastructure Channels." Proceedings of the 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018, Bologna, ITA Institute of Electrical and Electronics Engineers Inc., 2018. 68-72.
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