Equalization and interference cancellation in linear multiuser systems based on second-order statistics

Potential applications of blind channel identification and equalization in data communication systems have recently been explored. For multiuser syste ms that are irreducible and column-reduced, second-order statistical method s normally can identify channel dynamics up to a unitary mixing matrix. Add itional user separation (equalization) can rely on higher order statistics and other prior information. In this paper, we investigate the equalizabili ty of user signals and the cancellation of unwanted interfering signals bas ed only on second-order output statistics. We show that a user channel can be equalized if it has the longest memory. Furthermore, interfering user si gnals can be cancelled under a more relaxed multiuser channel condition.