Dynamic MIMO channel modeling in urban environment using particle filtering

MIMO transmission technologies have been the essential component in the cellular system such as LTE and LTE-Advanced. Recently, the communication performance evaluations of mobile users in the cellular MIMO system have become the great concern. In this paper, we propose the dynamic MIMO channel modeling for the urban environment. Our proposal is based on the Geometry-based Stochastic Channel Modeling. The cluster parameters such as the local scatterer locations around Rx are estimated from the measured data using the particle filtering. We carried out the 3.35GHz channel measurement in the urban environment, and we generated the dynamic channel from the measured data. The experiments showed that both the spreads and the auto-correlation of ToA, AoA and AoD were correctly reconstructed in our dynamic channel model.