Performance of a Novel Automatic Identification Algorithm for the Clustering of Radio Channel Parameters
| Autor: | Martine Lienard, Jose-Maria Molina-Garcia-Pardo, Maria-Teresa Martinez-Ingles, Davy P. Gaillot, Shiqi Cheng, Pierre Degauque |
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| Přispěvatelé: | Dpto. Tecnologías de la Información y las Comunicaciones, Universidad Politécnica de Cartagena / Technical University of Cartagena (UPCT), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF), Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN (TELICE - IEMN), Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF), Technical University of Cartagena (UPTC), Télécommunication, Interférences et Compatibilité Electromagnétique (IEMN-TELICE) |
| Rok vydání: | 2015 |
| Předmět: |
General Computer Science
Computer science General Engineering multipath component distance [SPI]Engineering Sciences [physics] Condensed Matter::Materials Science Robustness (computer science) cluster visibility index General Materials Science Radio channel lcsh:Electrical engineering. Electronics. Nuclear engineering Cluster analysis K-means lcsh:TK1-9971 Algorithm ComputingMilieux_MISCELLANEOUS Multipath propagation k-medians clustering clustering Communication channel |
| Zdroj: | IEEE Access IEEE Access, 2015, 3, pp.2252-2259. ⟨10.1109/ACCESS.2015.2497970⟩ IEEE Access, IEEE, 2015, 3, pp.2252-2259. ⟨10.1109/ACCESS.2015.2497970⟩ IEEE Access, Vol 3, Pp 2252-2259 (2015) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2015.2497970 |
| Popis: | A multipath component distance (MCD)-based automatic clustering identification algorithm is proposed to group multipath components (MPCs) obtained from radio channels. The developed algorithm iteratively and dynamically assigns the MPCs to the best cluster thanks to the MCD metric. Its performance and robustness are compared with the K-means MCD algorithm using cluster data simulated with four reference scenarios of the WINNER II channel model. The results indicate that K-means MCD is outperformed for all investigated scenarios in spite of its having a lower computational complexity and faster convergence. Moreover, a by-product of the algorithm is an optimal MCD threshold, that is, the characteristic of the cluster statistical properties for a given propagation scenario. This parameter provides a stronger physical link between the MPCs distribution and the propagation scenario. Therefore, it could be introduced in radio channel models with clusterlike features. |
| Databáze: | OpenAIRE |
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