High Speed Convergence of Blind Equalization

Abstract

In this paper, several methods to achieve fast on-line algorithms for blind equalization are developed. Firstly, the dead zone function on equalizer output is used to accelerate the convergence speed of the conventional distribution matching algorithm. Secondly, Godard's method is applied over the dead zone schemes. Furthermore, based on the asymptotic approach for the design of cost funtion, higher speed adaptive algorithm is derived and it is shown that the dead zone is reasonable for the case that the transmitted signal depends on the uniform distribution. The present cost function is designed to give the most precise estimate ω^L obtained from L samples of received signal in the sense that asymptotic covariance lim_L→∞ E [L (ω^L-ω^*) (ω^L-ω^*) ^T] is minimized, where ω^* is the ideal equalizer. Several computer simulations show that this cost function is generally effective to accelerate the convergence speed of on-line algorithms.