MIMO ISI Channel Estimation Using Uncorrelated Golay Complementary Sets of Polyphase Sequences

In this paper, optimal training sequence design for multiple-input multiple-output (MIMO) intersymbol interference channels is addressed, and several novel low-complexity channel estimators are proposed, using uncorrelated Golay complementary sets of polyphase sequences. A polyphase sequence is a sequence of complex numbers, each of unit magnitude. The theoretical analysis and simulation show that, when the additive noise is Gaussian, the proposed best linear unbiased estimator achieves the minimum possible classical Cramer-Rao lower bound (CRLB) if the channel coefficients are regarded as unknown deterministics. On the other hand, the proposed linear minimum mean-square error estimator attains the minimum possible Bayesian CRLB when the underlying channel coefficients are Gaussian and independent of the additive Gaussian noise. The proposed channel estimators not only achieve the best estimation performance but can also be implemented with low complexity via DSP or application-specified integrated circuit/field programmable gate array. This has been possible due to the special structures intrinsic to uncorrelated Golay complementary sets of polyphase sequences, which make the proposed channel estimators ready to use in the practical MIMO systems.