Datasets for Multipath Clustering at 285 MHz and 5.3 GHz Bands Based on COST 2100 MIMO Channel Model

Blanza, Jojo F.; Teologo, Antipas T.; Materum, Lawrence

doi:10.1109/ismac.2019.8836143

Cited by 14 publications

(18 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data set used in this study is extracted from the IEEE data port presented in [33]. Datasets were first extracted from the COST2100 Channel Model [34].…”

Section: Results and Analysesmentioning

confidence: 99%

Projection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques

Africa¹,

Trinidad²,

Materum³

2020

Adv. sci. technol. eng. syst. j.

Self Cite

View full text Add to dashboard Cite

“…The data set used in this study is extracted from the IEEE data port presented in [33]. Datasets were first extracted from the COST2100 Channel Model [34].…”

Section: Results and Analysesmentioning

confidence: 99%

Projection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques

Africa¹,

Trinidad²,

Materum³

2020

Adv. sci. technol. eng. syst. j.

Self Cite

View full text Add to dashboard Cite

“…where s MS is the antenna steering vector at MS and s BS is the antenna steering vector at BS. The dataset [14,15] is generated by C2CM, which consist of two indoor and six semi-urban channel scenarios as follows: [22] AOA (Z AOA W), and the whitened delay (delay W). The reference cluster identifications of the data are given by refclusID, which serves as the ground truth in evaluating the performance of the clustering approach.…”

Section: Cost 2100 Channel Model (C2cm) Datasetmentioning

confidence: 99%

“…DCT is performed to the datasets to overcome the problem of the circular nature of the angular domain. At the same time, WT is applied to the dataset to eliminate the issues on units and standardized the dataset [14]. The corresponding graphs of the transformed multipaths and the Figure 6.…”

Section: Graphical User Interface (Gui)mentioning

confidence: 99%

“…Some lack analysis platform [2]- [4] unlike those in [5]- [13]. In this paper, a GUI is developed to manage the data and results of clustering European Cooperation in Science and Technology (COST) 2100 dataset [14,15] using Modified Simultaneous Clustering and Model Selection (MSCAMSMA) [16]. The interface is an effective method in visualizing the COST 2100 dataset and the clustering results.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Interface for Visualization of Wireless Propagation Multipath Clustering Outcomes

Blanza¹,

Materum²

2020

Adv. sci. technol. eng. syst. j.

Self Cite

View full text Add to dashboard Cite

A graphical user interface (GUI) is presented to visualize the multipaths generated by COST 2100 channel model (C2CM) and the results of clustering the wireless propagation multipaths using Modified Simultaneous Clustering and Model Selection (MSCAMSMA). The usual practice of authors is to show their data and results using figures, tables, and graphs which are already sufficient to present their studies. However, the manner of displaying the data and results is static; that is, the user cannot examine them to analyze further the relationship of the different variables involved in the study. The paper presents a step further by showing dynamically the data and results which the user can manipulate according to its needs.

show abstract

“…It also group similar data together [5]- [16]. In our previous works [17]- [20], Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) [21] and Divergence-Based Clustering (DDC) [22] were used to cluster the dataset [23,24] generated by C2CM. In this work, the comparison of the clustering accuracy of SCAMSMA and DDC are presented.…”

Section: Introductionmentioning

confidence: 99%

Variation Between DDC and SCAMSMA for Clustering of Wireless MultipathWaves in Indoor and Semi-Urban Channel Scenarios

Blanza¹,

Materum²

2020

Adv. sci. technol. eng. syst. j.

Self Cite

View full text Add to dashboard Cite

The performance of Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) and Deep Divergence-Based Clustering (DDC) in clustering wireless multipaths generated by COST 2100 channel model (C2CM) is compared. Enhancing the accuracy of clustering multipaths is an open area of research which the clustering approaches try to improve. Jaccard index is used as the clustering validity metric of the clustering approaches. The results of the clustering approaches are compared using the analysis of variance (ANOVA) toolbox of MATLAB and displayed using the box plots. Results show that the cluster-wise Jaccard index is different between SCAMSMA and DDC for indoor scenarios, while the membership-wise Jaccard index is not. On the other hand, the cluster-wise Jaccard index is not different between the clustering approaches for semi-urban scenarios, while the membership-wise Jaccard index is a little different. The clustering approaches can be used in indoor scenarios based on accuracy.

show abstract

Datasets for Multipath Clustering at 285 MHz and 5.3 GHz Bands Based on COST 2100 MIMO Channel Model

Cited by 14 publications

References 12 publications

Projection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques

Projection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques

Interface for Visualization of Wireless Propagation Multipath Clustering Outcomes

Variation Between DDC and SCAMSMA for Clustering of Wireless MultipathWaves in Indoor and Semi-Urban Channel Scenarios

Contact Info

Product

Resources

About