RIA: Innovative Design and Analysis of Blind Adaptive Equalization Systems

盲自适应均衡器是实现高速数据传输的重要技术 消除线性失真的数字通信系统 非理想和带宽受限的信道。通过删除线性通道 没有训练序列的帮助下的失真，盲 均衡使发射机无需中断 正常的数据传输，以便生成训练信号 为了一个新调谐的接收器。尽管有太多的 现有的盲均衡方案，很少表现出所需的全球 收敛性许多现有的盲均衡器倾向于 不期望的局部收敛对应于很少或没有 符号间干扰消除，如前所述的作品 主要研究者和其他人。此外该 许多现有算法的收敛速度非常慢。 这项研究的主要目的是提高 性能的盲均衡系统，通过设计新的和 更好的盲均衡算法。 将利用各种线性和非线性约束， 快速开发、分析和测试，并实现全球融合 均衡算法 PAM/QAM的循环平稳特性 调制通道输出将被利用，以产生创新的 盲均衡器的设计。此外，各种随机 动态系统分析工具（如概率和随机 过程，频谱分析，平均和稳定性理论）将 在这项研究中继续被利用，因为它已经在许多 以前的适应性系统研究。然而，与大多数 以前的研究，循环平稳信号分析也将是 在盲均衡器的设计中使用， 通道输出的循环平稳性。 拟议的研究旨在扩大 盲自适应均衡的概念及其应用 广播数字通信系统，预计将有 直接和间接影响， 自适应系统在诸如自适应系统控制的领域中， 机器人、阵列处理、机械和航空航天工程， 和地球物理信号处理。

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.