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The optimal design of training sequences for channel estimation in multiple-input multiple-output (MIMO) systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model with spatial correlation known at both the transmitter and the receiver. To minimize the channel estimation error, optimal training sequences are designed to exploit full information of the spatial correlation under the criterion of minimum mean square error (MMSE). It is investigated that the spatial correlation is helpful to decrease the estimation error and the proposed training sequences have good performance via simulations.
The optimal design of training sequences for channel estimation in multiple-input multiple-output (MIMO) systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model with spatial correlation known at both the transmitter and the receiver. To minimize the channel estimation error, the optimal training sequences are designed to exploit full information of the spatial correlation under the criterion of minimum mean square error (MMSE). It is investigated that the spatial correlation is helpful to reduce the estimation error and the draft training sequences have good performance via simulations.