RIA: Innovative Design and Analysis of Blind Adaptive Equalization Systems

点击翻译按钮获取中文摘要

Blind adaptive equalizers are important elements in high data rate digital communication systems to remove linear distortions incurred by nonideal and bandlimited channels. By removing linear channel distortions without the aid of a training sequence, blind equalization makes it unnecessary for the transmitter to interrupt the normal data transmission in order to generate a training signal for the sake of a newly tuned receiver. Despite the plethora of existing blind equalization schemes, few exhibit the desired global convergence property. Many existing blind equalizers are prone to undesirable local convergence corresponding to little or no intersymbol interference removal, as shown in the previous works by the principal investigator and others. In addition, the convergence rates of many of the existing algorithms are very slow. A principal objective of this research is to improve the performance of blind equalization systems by designing new and better blind equalization algorithms. Various linear and nonlinear constraints will be utilized in developing, analyzing and testing fast and globally convergent equalization algorithms. The cyclostationary nature of the PAM/QAM modulated channel output will be exploited to generate innovative designs of blind equalizers. In addition, various stochastic dynamic systems analysis tools (such as probability and stochastic processes, spectral analysis, averaging and stability theory) will continue to be exploited in this study, as it has been in many previous adaptive system studies. However, unlike most of the previous studies, cyclostationary signal analysis will also be utilized in the design of blind equalizers based on the cyclostationarity of the channel output. The proposed research is aimed at expanding the utility of the concept of blind adaptive equalization and applications of broadcast digital communication systems, and is expected to have significant direct and indirect impact on the application of adaptive systems in areas such as adaptive system control, robotics, array processing, mechanical and aerospace engineering, and geophysical signal processing.