Improving the convergence rate of blind equalization using transform domain

In this paper we consider the blind equalization in the transform domain. For blind equalization, three blind algorithms, General Sato Algorithm, Constant Modulus Algorithm, Multimodulus Algorithm , which are known to be very efficient from implementation issues, are used. To improve the rate of convergence, we used the band-partitioning property of transform domain (TD). In fact, the TD causes the channel output samples to be uncorrelated and this increases the rate of convergence. Also, to further improve the rate of convergence, an optimal time variant step size is used. Simulation results are presented to show the fast convergence of the proposed blind equalizer.