CCA based algorithms for blind equalization of FIR MIMO systems

In this work the problem of blind equalization of multiple-input multiple-output (MIMO) systems is formulated as a set of canonical correlation analysis (CCA) problems. CCA is a classical tool that finds maximally correlated projections of several data sets, and it is typically solved using eigendecomposition techniques. Recently, it has been shown that CCA can be alternatively viewed as a set of coupled least squares regression problems, which can be solved adaptively using a recursive least squares (RLS) algorithm. Unlike other MIMO blind equalization techniques based on second-order statistics (SOS), the CCA-based algorithms does not require restrictive conditions on the spectral properties of the source signals. Some simulation results are presented to demonstrate the potential of the proposed CCA-based algorithms