Abstract:
In high speed voiceband modems, as in many other data transmission systems, linear distortion and additive noise are important degrading factors. The tapped-delay-line equalizers designed to minimize the mean-square-error cost function are commonly used to compensate these undesired effects. Among the several algorithms which minimizes the mean-square-error cost function stochastic gradient algorithm is the most popular because of its simplicity in implementation. However, for highly distorted channels stochastic gradient algorithm converges slowly and, therefore, a long training period which causes a fall in the overall performance of the system is required. Instead, more complicated algorithms with faster rate of convergence have been developed in the last years: Kalman/Godard, Fast Kalman and lattice algorithms. In this thesis, the rate of convergence of stochastic gradient, Kalman/Godard and Fast Kalman algorithms are analyzed and their computational, complexities are examined. The analysis is extended to the complex domain in order to cover equalization of quadrature-amplitude-modulated signals. Furthermore, a computer program package which simulates several telephone channels, a quadrature-amplitude-modulatiqn. system and the equalization algorithms is written. Them, the performance of the different equalizatIon algorithms over a wide range of channels are compared.