Cyclic Equalization-A New Rapidly Converging Equalization Technique for Synchronous Data Communication

Abstract

A new technique for very fast start-up of adaptive transversal-filter equalizers used in high-speed synchronous data communications is presented. A special training sequence whose period in symbols is equal to the number of equalizer taps is used initially to achieve an open eye pattern. Rapid convergence, even over highly distorted channels, is obtained because an ideal reference sequence is available at the receiver, but it is not necessary to synchronize the ideal reference with the received sequence. The special choice of the training sequence automatically provides the synchronized ideal reference needed for fast convergence, but the resulting equalizer coefficients may be cyclically displaced from their proper positions. After the eye is opened by this process, the equalizer coefficients are rotated to their proper positions, and decision-directed equalization is used with either a longer training sequence or random data to achieve final tap settings. Adjustments during the training period can be made with a gradient-type algorithm or with stochastic adjustment techniques; an exact analysis is possible for both of these schemes. Cyclic equalization is shown to provide perfect equalization at evenly spaced points in the frequency domain.