Grouping of COST 2100 indoor multipaths using simultaneous clustering and model selection
Simultaneous Clustering and Model Selection (SCAMS) is introduced to cluster multipaths from COST 2100 channel model (C2CM). SCAMS determines not only the number of clusters but also the membership of the clusters. The study is the first to report clustering of multipaths that consider simultaneousl...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2019
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2595 |
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| Institution: | De La Salle University |
| Summary: | Simultaneous Clustering and Model Selection (SCAMS) is introduced to cluster multipaths from COST 2100 channel model (C2CM). SCAMS determines not only the number of clusters but also the membership of the clusters. The study is the first to report clustering of multipaths that consider simultaneously the number of clusters and the membership of the clusters. Cluster identification and cardinality classification are dependent on the values of λ and γ, the parameters that weigh the penalty terms to avoid the trivial solution (all 1 matrix) of the affinity matrix. The clustered multipaths are compared with the reference multipaths that can be found in IEEE DataPort. The accuracy of the clustering approach is examined using the Jaccard index (η). The proposed clustering approach can achieve higher accuracy compared to popular multipath clustering approaches. © 2019, World Academy of Research in Science and Engineering. All rights reserved. |
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