Interference cancellation and blind equalization for linear multi-user systems

Potential applications of blind channel identification and equalization in wireless communication systems have been previously explored. For multi-user systems that are irreducible and column-reduced, second order statistical methods normally can identify channel dynamics up to a unitary mixing matrix. We investigate the equalizability of desired users and the cancellation of unwanted interfering signals based on second order output statistics. We show that a desired user channel can be equalized if it has the longest memory. Furthermore, interfering user signals can be cancelled under a more related multi-user channel condition