Detection and Tracking of MIMO Propagation Path Parameters Using State-Space Approach

This paper describes a novel approach for detection, estimation and tracking of multiple-input multiple-output (MIMO) radio propagation parameters from multidimensional channel sounding measurements. A realistic state-space model is developed for the purpose, and the extended Kalman filter (EKF) is applied in a particular computationally efficient form to track the geometrical double-directional propagation path parameters. The observation model utilizes the dense multipath component (DMC), describing the distributed scattering in the channel, as part of the underlying noise process. The DMC model assumes an exponential profile in delay, and allows for an arbitrary angular distribution. In addition, a novel dynamic state dimension estimator using statistical goodness-of-fit tests is introduced. The employed methods are supported by illustrative estimation examples from MIMO channel sounding measurements.