Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques

Designing wireless communication systems requires a knowledge of the propagation environment which is addressed by using channel models. Cluster-based channel models are nowadays used to develop and evaluate wireless networks based on groups of multipath components (MPCs) with similar parameters cal...

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Main Author: Trinidad, Emmanuel T.
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Language:English
Published: Animo Repository 2022
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Online Access:https://animorepository.dlsu.edu.ph/etdm_ece/13
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etdm_ece-1012
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spelling oai:animorepository.dlsu.edu.ph:etdm_ece-10122022-07-21T23:20:30Z Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques Trinidad, Emmanuel T. Designing wireless communication systems requires a knowledge of the propagation environment which is addressed by using channel models. Cluster-based channel models are nowadays used to develop and evaluate wireless networks based on groups of multipath components (MPCs) with similar parameters called clusters. Clustering the MPCs has been widely studied using different algorithms to cluster MPC automatically, resulting in different accuracy. This study improves clustering results through visualization with Dimensionality Reduction (DR) algorithmic techniques namely t-SNE and UMAP and a graphical user interface (GUI) that projects the MPCs to interactively refine the cluster membership accuracy. Generated clustering results from the Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) and the COST 2100 Channel Model (C2CM) data serves as ground truth to test the effectiveness of visualizations along with the Jaccard index and Adjusted Rand Index (ARI) for validation. This work achieves a 0.3368 at 10th percentile, a median of 0.4697, and 0.8884 at 90th percentile of Jaccard membership index for all the datasets, which are vis-a-vis improved the SCAMS result. 2022-07-01T07:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdm_ece/13 Electronics And Communications Engineering Master's Theses English Animo Repository Wireless communication systems MIMO systems Electrical and Electronics Systems and Communications
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Wireless communication systems
MIMO systems
Electrical and Electronics
Systems and Communications
spellingShingle Wireless communication systems
MIMO systems
Electrical and Electronics
Systems and Communications
Trinidad, Emmanuel T.
Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
description Designing wireless communication systems requires a knowledge of the propagation environment which is addressed by using channel models. Cluster-based channel models are nowadays used to develop and evaluate wireless networks based on groups of multipath components (MPCs) with similar parameters called clusters. Clustering the MPCs has been widely studied using different algorithms to cluster MPC automatically, resulting in different accuracy. This study improves clustering results through visualization with Dimensionality Reduction (DR) algorithmic techniques namely t-SNE and UMAP and a graphical user interface (GUI) that projects the MPCs to interactively refine the cluster membership accuracy. Generated clustering results from the Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) and the COST 2100 Channel Model (C2CM) data serves as ground truth to test the effectiveness of visualizations along with the Jaccard index and Adjusted Rand Index (ARI) for validation. This work achieves a 0.3368 at 10th percentile, a median of 0.4697, and 0.8884 at 90th percentile of Jaccard membership index for all the datasets, which are vis-a-vis improved the SCAMS result.
format text
author Trinidad, Emmanuel T.
author_facet Trinidad, Emmanuel T.
author_sort Trinidad, Emmanuel T.
title Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
title_short Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
title_full Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
title_fullStr Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
title_full_unstemmed Visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
title_sort visualization assisted interactive wireless multipath clustering using dimensionality reduction techniques
publisher Animo Repository
publishDate 2022
url https://animorepository.dlsu.edu.ph/etdm_ece/13
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