A study on blind equalization techniques.

Author(s)

Magno Teófilo Madeira da Silva

• Document type: Doctoral Thesis
• Press: São Paulo.
• Institution: Universidade de São Paulo (USP). Escola Politécnica (EP/BC)
• Defense date: 2005-01-17

Examining board members

Maria das Dores dos Santos Miranda; Jose Carlos Moreira Bermudez; Phillip Mark Seymour Burt; Marcello Luiz Rodrigues de Campos; Vitor Heloiz Nascimento

• Advisor: Maria das Dores dos Santos Miranda

Abstract

The equalization of communication channels is addressed by using blind techniques based on higher order statistics. A step-size interval is obtained to ensure the convergence of Steepest-Descent Constant Modulus Algorithm. The Shalvi-Weinstein Algorithm (SWA) and Constant Modulus Algorithm (CMA) are revisited and their tracking capabilities are analyzed by using an energy conservation relation. Moreover, a novel blind algorithm named Accelerated Constant Modulus Algorithm (AC-CMA) is proposed. It adjusts the second derivative (“acceleration") of the coefficient estimates and presents a more favorable compromise between computational complexity and convergence rate than CMA or SWA. These results are extended to the MIMO (Multiple-Input Multiple-Output) case. By means of simulations, the algorithms are compared and the convergence and tracking analysis are validated. The Decision Feedback Equalizer (DFE) is considered in the SISO (Single-Input Single-Output) case with the Constant Modulus criterion and a concurrent algorithm is proposed. It avoids degenerated solutions and shows better behavior than the others presented in the literature. In order to avoid error propagation, a hybrid DFE is also proposed. It includes a recurrent neural network in the feedback filter and may be advantageously used to equalize linear and nonlinear channels. (AU)