On training fractionally spaced equalizers using intersymbol interpolation

The use of an intersymbol interpolation method in training fractionally spaced equalizers (FSEs) is investigated. It is shown that the optimal interpolation filter depends on the amplitude frequency response of the transmitter filter and the channel. Using a nonoptimal interpolation filter increases the stead-state mean-square error of the FSE. An interpolated complex FSE (CFSE) using a stochastic gradient, or LMS, adaptive algorithm has very little advantage over an LMS CFSE with symbol-rate updating. However, an interpolated LMS phase-splitting FSE (PS-FSE) has a convergence speed that is twice as fast as a conventional PS-FSE. Special precautions for evaluating the performance of interpolated FSEs are discussed, and a novel evaluation scheme is proposed