Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum
Radio channel propagation models for the millimeter wave (mmWave) spectrum are extremely important for planning future 5G wireless communication systems. Transmitted radio signals are received as clusters of multipath rays. Identifying these clusters provides better spatial and temporal characterist...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-09-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/10/9/287 |
| _version_ | 1818855797041397760 |
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| author | Bogdan Antonescu Miead Tehrani Moayyed Stefano Basagni |
| author_facet | Bogdan Antonescu Miead Tehrani Moayyed Stefano Basagni |
| author_sort | Bogdan Antonescu |
| collection | DOAJ |
| description | Radio channel propagation models for the millimeter wave (mmWave) spectrum are extremely important for planning future 5G wireless communication systems. Transmitted radio signals are received as clusters of multipath rays. Identifying these clusters provides better spatial and temporal characteristics of the mmWave channel. This paper deals with the clustering process and its validation across a wide range of frequencies in the mmWave spectrum below 100 GHz. By way of simulations, we show that in outdoor communication scenarios clustering of received rays is influenced by the frequency of the transmitted signal. This demonstrates the sparse characteristic of the mmWave spectrum (i.e., we obtain a lower number of rays at the receiver for the same urban scenario). We use the well-known <i>k</i>-means clustering algorithm to group arriving rays at the receiver. The accuracy of this partitioning is studied with both cluster validity indices (CVIs) and score fusion techniques. Finally, we analyze how the clustering solution changes with narrower-beam antennas, and we provide a comparison of the cluster characteristics for different types of antennas. |
| first_indexed | 2024-12-19T08:14:18Z |
| format | Article |
| id | doaj.art-85baf4ec502749feb3587052e63dd431 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-19T08:14:18Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-85baf4ec502749feb3587052e63dd4312022-12-21T20:29:32ZengMDPI AGInformation2078-24892019-09-0110928710.3390/info10090287info10090287Clustering Algorithms and Validation Indices for a Wide mmWave SpectrumBogdan Antonescu0Miead Tehrani Moayyed1Stefano Basagni2Institute for the Wireless Internet of Things, Northeastern University, Boston, MA 02115, USAInstitute for the Wireless Internet of Things, Northeastern University, Boston, MA 02115, USAInstitute for the Wireless Internet of Things, Northeastern University, Boston, MA 02115, USARadio channel propagation models for the millimeter wave (mmWave) spectrum are extremely important for planning future 5G wireless communication systems. Transmitted radio signals are received as clusters of multipath rays. Identifying these clusters provides better spatial and temporal characteristics of the mmWave channel. This paper deals with the clustering process and its validation across a wide range of frequencies in the mmWave spectrum below 100 GHz. By way of simulations, we show that in outdoor communication scenarios clustering of received rays is influenced by the frequency of the transmitted signal. This demonstrates the sparse characteristic of the mmWave spectrum (i.e., we obtain a lower number of rays at the receiver for the same urban scenario). We use the well-known <i>k</i>-means clustering algorithm to group arriving rays at the receiver. The accuracy of this partitioning is studied with both cluster validity indices (CVIs) and score fusion techniques. Finally, we analyze how the clustering solution changes with narrower-beam antennas, and we provide a comparison of the cluster characteristics for different types of antennas.https://www.mdpi.com/2078-2489/10/9/287mmWaveclustering algorithmscluster validity indiceschannel propagation models |
| spellingShingle | Bogdan Antonescu Miead Tehrani Moayyed Stefano Basagni Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum Information mmWave clustering algorithms cluster validity indices channel propagation models |
| title | Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum |
| title_full | Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum |
| title_fullStr | Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum |
| title_full_unstemmed | Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum |
| title_short | Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum |
| title_sort | clustering algorithms and validation indices for a wide mmwave spectrum |
| topic | mmWave clustering algorithms cluster validity indices channel propagation models |
| url | https://www.mdpi.com/2078-2489/10/9/287 |
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