Propagation Parameter Tracking using Variable State Dimension Kalman Filter

The development of future wireless communication systems requires modeling of the radio propagation environment. These models need the estimation of the model parameters from channel sounding measurements. In this paper, we build a state-space model, and estimate the propagation parameters with the extended Kalman filter in order to capture the dynamics of the channel parameters in time. The model also includes the effect of distributed diffuse scattering in radio channels. The issue of varying state variable dimension, i.e., the number of propagation paths to track, is investigated. For this purpose, we rely also on maximum likelihood based estimation techniques. The proposed algorithm is investigated using both simulated and measured data