Efficient tracking of eigenspaces and its application to eigenbeamforming

To achieve high performance for MIMO wireless systems with multiple transmit and receive antennas a detailed understanding of the characteristics of the eigenspace of the channel is essential. It represents the spatial characteristics of the propagation scenario in general and can be expressed by different covariance matrices of the channel coefficients. In many MIMO-algorithms the knowledge of the eigenvectors and eigenvalues is required. As typical for the wireless channel, the spatial characteristics continuously change. Therefore, an efficient method for tracking the eigenspace with moderate computational complexity is required. Tracking of the eigenspace using incremental Jacobi rotations is presented and compared to other known algorithms for subspace tracking. Eigenbeamforming serves as an example, where such a tracking algorithm can be applied.