An improved block equalization scheme for uncertain channel estimation

We consider the design of a block equalizer for an intersymbol interference channel, given that the channel impulse response is not perfectly known at the receiver. In contrast to other schemes, our receiver is designed for imperfect channel state information and incorporates the statistics of the channel estimation error. In particular, we suggest an error model for data transmission that takes the influence from the data symbols on the estimation noise into account. We derive the optimum detection rule for the considered error model according to the maximum likelihood criterion and verify that the covariance matrix of the estimation noise depends on the actual transmitted data symbols. Motivated by this result, we propose a realizable receiver structure adopting the turbo principle that exploits the data-dependency of the covariance matrix of the estimation noise. The proposed scheme outperforms conventional receivers that neglect the exact statistics of the estimation noise. The core of our receiver is a soft-input soft-output block equalizer based on constrained minimum variance filter design. We assess the performance of the proposed turbo equalization scheme for block Rayleigh fading channels, applying both one-shot training-based channel estimation and iterative data-aided channel estimation