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件。自盲自适应均衡概念提出以来，在不到15年的时间里，各种算法已经被提出、实现、测试和安装，这些算法通常是针对特定的源星座类别量身定制的。收敛，尽管任意差的初始化，参数化接近最优可实现的性能是一个可接受的盲自适应均衡器算法，或任何参数自适应系统的一个看似理想的属性。显然，目前已知的有限脉冲响应均衡器的盲自适应算法无法保证这一点，即使在具有完美恢复能力和最简单的正负数字源的理想情况下也是如此。然而，没有任何定理证明这样的全局收敛算法不存在，即使是在理想化的情况下。事实上，由于一些（看似）矛盾的说法，与这个问题相关的现有文献给人留下了复杂的印象。该研究解决了这一存在性问题，至少在包含当前最流行的盲自适应均衡器的无记忆误差函数类方案中是如此。在不具有可容许性（即全局渐近最优性）的被禁止的应用程序和算法类别中，将通过检查相关误差曲面的几何形状来研究这种不可容许性的实际后果的严重性。对于缺乏全局渐近最优性的方案，均衡器参数初始化方案的效用也将被研究。最后，将研究在已建立的缺乏全局渐近最优性的类之外的“新”方案的可接受性的潜力，例如，利用带有内存的错误函数的自适应算法。