A feedback analysis of the tracking performance of blind adaptive equalization algorithms

Uses feedback and system theory concepts to study the tracking performance of a widely used class of (nonlinear) adaptive algorithms for blind equalization. These algorithms are normally used in highly nonstationary environments (e.g., wireless fast fading channels), and it is therefore important to study their ability to track changes in the environment characteristics. Due to their inherent nonlinear nature, there have been essentially no results in the literature on the tracking performance of these algorithms. The approach proposed in this paper is based on studying the energy flow through a feedback cascade that is induced by any such adaptive algorithm. A key feature of the feedback approach is that it bypasses the need for working directly with the nonlinear recursion for the weight error vector of the adaptive equalizer