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An Improved K-Power Means Technique Using Minkowski Distance Metric and Dimension Weights for Clustering Wireless Multipaths in Indoor Channel Scenarios
- Source :
- Journal of ICT, Vol 20, Iss 4, Pp 541-563 (2021)
- Publication Year :
- 2021
- Publisher :
- UUM Press, 2021.
-
Abstract
- Wireless multipath clustering is an important area in channel modeling, and an accurate channel model can lead to a reliable wireless environment. Finding the best technique in clustering wireless multipath is still challenging due to the radio channels’ time-variant characteristics. Several clustering techniques have been developed that offer an improved performance but only consider one or two parameters of the multipath components. This study improved the K-PowerMeans technique by incorporating weights or loads based on the principal component analysis and utilizing the Minkowski distance metric to replace the Euclidean distance. K-PowerMeans is one of the several methods in clustering wireless propagation multipaths and has been widely studied. This improved clustering technique was applied to the indoor datasets generated from the COST 2100 channel Model and considered the multipath components’ angular domains and their delay. The Jaccard index was used to determine the new method’s accuracy performance. The results showed a significant improvement in the clustering of the developed algorithm than the standard K-PowerMeans.
- Subjects :
- General Computer Science
business.industry
Computer science
principal component analysis
General Mathematics
multipath clustering
Minkowski distance
Information technology
Topology
T58.5-58.64
Power (physics)
minkowski distance
Dimension (vector space)
radio wave propagation
Metric (mathematics)
Computer Science::Networking and Internet Architecture
Wireless
channel model
business
Cluster analysis
Communication channel
Computer Science::Information Theory
Subjects
Details
- Language :
- English
- ISSN :
- 21803862
- Volume :
- 20
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Journal of ICT
- Accession number :
- edsair.doi.dedup.....991095068541b85baf5566a38b5f8db6