Blind Adaptive Channel Equalization for QAM Source Signals

盲自适应均衡器是高速无线通信系统中的关键接收机部件。 高性能、高密度、数字通信系统。 不到 自盲自适应均衡的概念提出十五年以来， 各种算法，经常针对特定的源 星座类，已经提出，实施，测试和 安装. 收敛，尽管一个任意差的初始化，到一个 具有接近最佳可实现性能的参数化是一种 一个可接受的盲自适应均衡器的看似理想的属性 算法，或任何参数自适应系统。 显然没有盲自适应算法的有限脉冲响应 均衡器是已知的存在，可以保证这一点，即使是理想化的 具有完美的恢复能力和最简单的数字 加和减1的源。 然而，没有定理证明这样的一个 全局收敛算法不存在，即使在理想化的 设置. 事实上，与此问题相关的现有文献 由于一些（看似）矛盾的说法，给人留下了复杂的印象。 这项研究解决了这个存在的问题，至少在班级中是这样。 的计划与无记忆的错误功能，其中包括最 目前使用的流行盲自适应均衡器。 内 被禁止的一类应用程序和算法， 可受理性（即，全局渐近最优性）， 这一不可受理性的实际后果将由 检查相关误差表面的几何形状。 对于方案 均衡器参数的效用缺乏全局渐近最优性， 还将研究初始化方案。 最后 容许类别以外的“新”计划的可能性 建立缺乏全局渐近最优性将是 调查，例如，利用误差函数的自适应算法 有记忆

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.