EFFICIENT TRACKING OF EIGENSPACES AND ITS APPLICATION TO MIMO-SYSTEMS

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. In many MIMOalgorithms the knowledge of the Eigenvectors and Eigenvalues are required. As typical for the wireless channel, the spatial characteristics continuously change. Therefore, an efficient method for tracking of the Eigenspace with moderate computational complexity is required. Tracking of the Eigenspace using incremental Jacobi rotations is presented and compared to another known algorithm for subspace tracking. Eigenbeamforming and reduced dimension MIMO-channel estimation serve as two examples, where such a tracking algorithm can be applied. Complexity evaluations show the capabilities of the Jacobi-tracking.

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