Adaptive Multi-Input Multi-Output Fading Channel Equalization Using Kalman Estimation

Absrrucr-This paper addresses the problem of adaptive channel tracking and equalization for multi-input multi-output (MIMO) time-variant frequency-selective channels. A finite-length minimum-mean-squarederror decision-feedback equalizer (MMSE-DFE) performs the equalization task, while a Kalman filter tracks the MIMO channel, which models the corrupting effects of inter-symbol interference @SI), inter-user interference @VI), and noise. The Kalman tracking is aided by previous hard decisions produced by the DFE, with a decision delay A > 0, which causes the Kalman filter to track the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multi-user fading IS1 channels at the expense of higher complexity.