New results on second-order statistics-based blind identification and equalization of SIMO channels

Blind channel estimation and blind equalization of SIMO (single-input multiple-output) communications channels is considered using only the second-order statistics of the data. Estimation of (partial) channel impulse response and design of finite-length MMSE (minimum mean-square error) blind equalizers is investigated. The basis of the approach is the design of multiple zero-forcing equalizers that whiten the noise-free data at multiple delays. In the past such an approach has been considered using just one zero-forcing equalizer at zero-delay. Infinite impulse response (IIR) channels are allowed. The proposed approach also works when the "subchannel" transfer functions have common zeros so long as the common zeros are minimum-phase zeros. The channel length of model orders need not be known. An illustrative simulation example is provided.