RIA: Innovative Design and Analysis of Blind Adaptive Equalization Systems

盲自适应均衡器是高数据速率数字通信系统中消除非理想信道和带宽受限信道引起的线性失真的重要器件。通过消除线性信道失真而不借助训练序列，盲均衡使得发送端不必中断正常的数据传输来为新调谐的接收端生成训练信号。尽管已有大量的盲均衡方案，但很少有方案具有理想的全局收敛性。许多现有的盲均衡器容易出现不理想的局部收敛，对应于很少或没有去除符号间干扰，正如首席研究员和其他人之前的工作所示。此外，现有的许多算法的收敛速度非常慢。本研究的主要目的是通过设计新的、更好的盲均衡算法来提高盲均衡系统的性能。各种线性和非线性约束将被用于开发、分析和测试快速和全局收敛的均衡算法。PAM/QAM调制信道输出的周期平稳特性将被用于产生盲均衡器的创新设计。此外，各种随机动态系统分析工具（如概率和随机过程，谱分析，平均和稳定性理论）将继续在本研究中被利用，因为它已经在许多以前的自适应系统研究中得到了利用。然而，与之前的大多数研究不同的是，循环平稳信号分析也将用于基于信道输出的循环平稳设计盲均衡器。本研究旨在扩大盲自适应均衡概念的应用范围和广播数字通信系统的应用，并有望对自适应系统在自适应系统控制、机器人技术、阵列处理、机械和航空航天工程等领域的应用产生重大的直接和间接影响。地球物理信号处理。

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.