Evaluation of the effects of intersymbol interference in decision-feedbackequalizers

For channels which suffer predominantly from additive noise and intersymbol interference, the decision-feedback equalizer has provided a relatively si mple solution for reducing the effects of interfering symbols at the input to the decision device, In this paper, a technique is developed that enable s fast, accurate calculation of the error performance of decision-feedback equalization for a number of channel models. The method is to calculate the n-step transition probability for an associated Markov process and then us e this transition probability as an approximation to the stationary probabi lity distribution. For systems with finite memory, it is proved that the me thod converges, If the signal-to-noise ratio (SNR) is high and the signal a mplitude is more than twice the worst-case interference, it is shown that t he convergence is rapid. Numerical results indicate that the convergence is rapid enough to make this an efficient method of calculation, even for cha nnels for which the interference does not fully satisfy this condition. Two examples are given here, but the technique has been tested on most of the examples that have been presented in the literature. The method yields resu lts in closer agreement with simulation results than previous results obtai ned using bounding techniques, especially at low to moderate SNR's, and req uires less computation.