Affine Precoding-based Superimposed Training for Semi-Blind Channel Estimation in OSTBC MIMO-OFDM Systems

摘要

This paper develops a framework for semi-blind channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems that use orthogonal space-time block codes (OSTBCs). The proposed technique is based on a whitening unitary (WU) decomposition together with superimposed training (ST). The ST incorporates an orthogonal affine precoder to avoid interference between the pilot and data symbols during both channel estimation and data detection. The complex constrained Cramer-Rao bound (CC-CRB) is derived to characterize the resulting mean squared error (MSE) of the proposed semi-blind channel estimation scheme. Simulation results using practical IMT-2000 channel models demonstrate the improved performance of the proposed semi-blind scheme in comparison to both non-semiblind ST and conventional training techniques, in terms of the MSE and bit error rate (BER).