Equalization of time-varying MIMO systems using modified Kalman filter algorithm

A new approach to adaptive equalization of time-varying multiple input multiple output (MIMO) systems is proposed. Based on a derived state-space model to characterize the time-varying MIMO channels, we use modified Kalman filter algorithm to estimate and track the channel and use LS criterion and MMSE criterion to perform the equalization. Simulation results illustrate good performance of this method. Two modified Kalman filter algorithm can effectively overcome the problem of computational errors. LS criterion equalization requires a strong condition on channel transfer function but it is simple and needs less storage space. MMSE criterion equalization can be applied in broader practical scenarios, but the calculation of autocorrelation matrix is computationally burdensome and needs more storage space.