Blind Adaptive Channel Equalization for QAM Source Signals

QAM 源信号的盲自适应信道均衡

• 批准号: 8921003
• 负责人: C. Richard Johnson
• 金额: --
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-04-01 至 1992-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8921003&HistoricalAwards=false
• 关键词: Blind; Adaptive; Channel; Equalization; QAM

Blind adaptive equalizers are key receiver components in high performance, high density, digital communications systems. In less than fifteen years since the conception of blind adaptive equalization, various algorithms, frequently tailored to a particular source constellation class, have been proposed, implemented, tested and installed. Convergence, despite an arbitrarily poor initialization, to a parameterization with nearly optimum achievable performance is a seemingly desirable attribute of an acceptable blind adaptive equalizer algorithm, or of any parameter adaptive system for that matter. Apparently no blind adaptive algorithm for a finite-impulse-response equalizer is known to exist that can promise this, even for an idealized situation with perfect recovery capability and the simplest digital source of plus and minus ones. yet, no theorem proves that such a globally convergent algorithm does not exist, even in an idealized setting. Indeed, the available literature pertinent to this issue leaves a mixed impression due to some (seemingly) contradictory claims. The research addresses this existence question, at least among the class of schemes with memoryless error functions which subsumes the most popular blind adaptive equalizers currently in use. Within the proscribed class of applications and algorithms that do not posses admissibility (i.e., global asymptotic optimality), the severity of the practical consequences of this inadmissibility will be investigated by examining the geometry of the associated error surface. For schemes lacking global asymptotic optimality, the utility of equalizer parameter initialization schemes will also be investigated. Finally, the potential for admissibility of "new" schemes that are outside the class established which lacks global asymptotic optimality will be investigated, e.g., adaptive algorithms that utilize error functions with memory.

盲目自适应均衡器是高性能，高密度，数字通信系统中的关键接收器组件。 自盲目自适应均衡概念以来不到十五年，已经提出，实施，测试和安装了经常针对特定源星座类别的各种算法。 尽管初始化任意较差，但收敛性与几乎最佳性能的参数化是可接受的盲人自适应均衡器算法或任何参数自适应系统的理想属性。 显然，已知存在有限强度反应均衡器的盲目自适应算法可以保证这一点，即使对于具有完美恢复能力的理想情况和最简单的PLUS和减去数字源的理想情况也是如此。 但是，没有定理证明即使在理想化的环境中，这种全球收敛算法也不存在。 的确，由于某些（看似）矛盾的主张，与此问题有关的可用文献给人留下了不同的印象。 这项研究解决了这个存在问题，至少在具有无内存错误函数的方案类别中，这些功能涵盖了当前正在使用的最流行的盲目自适应均衡器。 在不可接受的应用程序和算法类别中（即全球渐近优化性）中，将通过检查相关误差表面的几何形状来研究这种不可接受性的实际后果的严重性。 对于缺乏全球渐近优化性的方案，还将研究均衡参数初始化方案的实用性。 最后，将研究缺乏全局渐近优化性的类“新”方案的可接受性，例如使用记忆使用错误函数的自适应算法。