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Tracking time-variant cluster parameters in MIMO channel measurements

Publiceringsår: 2007
Språk: Engelska
Publikation/Tidskrift/Serie: Proc. ChinaCom 2007
Dokumenttyp: Konferensbidrag


This paper presents a joint clustering-and-tracking

framework to identify time-variant cluster parameters for

geometry-based stochastic MIMO channel models.

The method uses a Kalman filter for tracking and predicting

cluster positions, a novel consistent initial guess procedure that accounts for predicted cluster centroids, and the well-known KPowerMeans algorithm for cluster identification. We tested the framework by applying it to two different sets of MIMO channel measurement data, indoor measurements conducted at 2.55 GHz and outdoor measurements at 300 MHz. The results from our joint clustering-and-tracking algorithm provide a good match with the physical propagation mechanisms observed in the measured scenarios.


  • Electrical Engineering, Electronic Engineering, Information Engineering
  • channel modeling
  • multipath cluster
  • MIMO



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