Blind channel equalization with colored source based on constrained optimization methods

The constrained minimum output variance method (CMOV), which is also known as the constrained minimum output energy method (CMOE), has been applied to directly blind equalize a linear channel and proven effective with white inputs (Tsaisanis et al. (1999)). It is believed that the method introduced in Tsaisanis can work for a linear system with colored source. In this paper, we correct this misunderstanding, and prove that a colored input will cause the equalizer to incorrectly converge. Consequently, we introduce a new blind channel equalizer algorithm based on the CMOV, but with different constraints. Our proposed algorithm works for channels with either white or colored input, and performs equivalently to the trained minimum mean-square-error (MMSE) equalizer under high SNR. Our proposed algorithm may be regarded as a generalized version of the CMOV in Tsaisanis. However, unlike CMOV, the proposed method exploits the input sequence statistics. As a result, the proposed method performs better than the original CMOV even when the input is white.