Documento de conferencia

Clustering of radio channel parameters: Evaluation of a novel automatic identification algorithm

Conference Proceeding cp
2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016 - Proceedings
  • Fecha: 25 octubre 2016
  • Páginas: 1687-1688
  • ISBN: 9781509028863
  • Tipo de fuente: Ponencia
  • DOI: 10.1109/APS.2016.7696550
  • Tipo de documento: Documento de conferencia
  • Editorial: Institute of Electrical and Electronics Engineers Inc.
© 2016 IEEE.A Multipath Component Distance (MCD) based Automatic Clustering Identification algorithm (ACId-MCD) is introduced to group multipath components (MPCs) obtained from radio channels. Its performance is 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. Moreover, a by-product of the algorithm is an optimal MCD threshold that is 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.

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