A reduced complexity MIMO Kalman equalizer architecture is proposed in this brief by jointly considering the displacement structure and the block-Toeplitz structure. Numerical matrix–matrix multiplications with O(F3) complexity are eliminated by simple data loading process, where is the spreading factor. Finally, an iterative Conjugate-Gradient based algorithm is proposed to avoid the inverse of the Hermitian symmetric innovation covariance matrix in Kalman gain processor. The proposed architecture not only reduces the numerical complexity from O(F2) to O(Flog2F) per chip, but also facilitates the parallel and pipelined VLSI implementation in real-time processing.