Modified SMI techniques for frequency selective channels in OFDM

The Sample Matrix Inversion (SMI) algorithm has been widely applied in the filed of adaptive antenna arrays. However, in Time Division Multiple Access (TDMA) systems with known data sequences, a low cost solution would imply the computation of the beamformer based exclusively on this data. In some cases, this might not be possible since the known data could not be sufficient to get a stable estimate of both the sample covariance matrix and the steering vector needed for the SMI spatial filter. In this paper, windowing techniques are applied in order to calculate a beamformer per subcarrier for Orthogonal Frequency Division Multiplexing (OFDM) systems with very limited known training. This approach is compared to the subcarrier grouping approach, and the presented results show that the former method provides a further performance gain, even in channels with high delay spread.