Blind channel estimation and equalization of multiple-input multiple-output channels

Channel estimation and blind equalization of MIMO (multiple-input multiple-output) communications channels is considered using primarily the second-order statistics of the data. We consider estimation of (partial) channel impulse response and design of finite-length MMSE (minimum mean-square error) blind equalizers. The basis of the approach is the design of a zero-forcing equalizer that whitens the noise-free data. We allow infinite impulse response (IIR) channels. Moreover, the multichannel transfer function need not be column-reduced. Our approaches also work when the “subchannel” transfer functions have common zeros so long as the common zeros are minimum-phase zeros. The channel length or model orders need not be known. The sources are recovered up to a unitary mixing matrix and are further `unmixed” using higher-order statistics of the data. An illustrative simulation example is provided