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Correlation properties of large scale parameters from 2.66 GHz multi-site macro cell measurements

Författare:
Publiceringsår: 2011
Språk: Engelska
Dokumenttyp: Konferensbidrag

Sammanfattning

Multi-site measurements for urban macro cells at 2.66 GHz are performed with three base stations and one mobile station. In order to analyze the correlation properties of large scale parameters, we split up the routes into subsets, where it can be assumed that wide-sense stationarity (WSS) applies. The autocorrelation distance and correlation properties of large scale parameters for each link are analyzed. By comparing these properties with the corresponding parameters from the COST 2100 and WINNER II models, we can see that the measured autocorrelation distance of the shadow fading as well the autocorrelation distance of delay spread have similar properties as in the two models. The shadow fading and delay spread from the same link are negatively correlated and match the two models well. Based on the WSS subsets, we can see that large scale parameters for different links can be correlated, also when two BSs are far away from each other. In those cases the correlation of different links tends to be positively correlated when both base stations are in the same direction compared to the movement of the MS, otherwise the two links are usually negatively correlated.

Disputation

Nyckelord

  • Technology and Engineering
  • Multi-site
  • correlation
  • large scale parameters
  • channel model
  • channel measurements

Övriga

2011 IEEE 73rd Vehicular Technology Conference (VTC Spring)
2011-05-15/2011-05-18
Budapest, Hungary
Published
Yes
  • Radio Systems
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • ISSN: 1550-2252
  • ISBN: 978-1-4244-8332-7

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