Independent component analysis for semi-blind signal separation in MIMO mobile frequency selective communication channels

In this paper we address the problem of semi-blind source separation (SBSS) in frequency selective MIMO mobile communication channels. Semi-blindness stems from the fact that some average properties of the time-varying channel (mixing domain) are available at the transmitter. In this paper we first analytically show that when orthogonal frequency division multiplexing (OFDM) is employed, the original BSS problem is transformed into a set of standard ICA problems with complex mixing matrices. Each ICA problem is associated with one of the orthogonal subcarriers. This is special case of performing ICA in frequency domain where no inverse Fourier transformation of the separated signals is necessary. Secondly, we show that the statistical correlation between the different frequency bins (at each orthogonal sub-carrier) can be exploited to avoid the frequency dependent permutation problem, intrinsic to the ICA solution. Our approach has been tested on a realistic channel model and the results are presented.