Adaptive Receivers for Uncertain, Time-Varying Channels

在这项研究中，我们的目标是开发一个非参数自适应通信接收机策略，利用结果从理论的普遍分类和数据压缩。基于数据的“典型性”的分析已经成为现代信息论中的主要理论和实践概念之一。所谓的“类型”（适当的直方图估计的幅度分布）不仅已被证明是足够的统计分类和压缩，但也已被证明是指数快速收敛到真正的底层分布。由于基于类型的检测器不对信道特性进行先验假设，并且测量提供渐近最佳接收所需的量，因此这些检测器理论上可以实现与千里眼接收器相同的指数错误率，千里眼接收器完美地了解信道特性并最佳地使用它们。在随后的传输期间进行的测量（可能使用判决反馈范例中的数据传输本身）可以用于跟踪信道变化。该方法将被扩展到处理样本间的依赖性和有色噪声，通过使用通道测量在一个最佳的有效方式。从数据压缩工作，上下文树和Lempel-Ziv（通用）编码，两种技术得出，将检查，以确定哪一个代表通道诱导的依赖关系最有效，哪一个是最适应。通过合并基于这两种理论的系统，将开发出适应未知时变信道的接收机。它将被证明，这种接收机可以用于多用户信道，无线和光纤，很少修改。该研究将开发这种自适应接收器策略的理论基础，并将开发一个完整的软件实现的接收器，作为测试数据的实际通信信道记录。 这项工作将由莱斯大学和乔治梅森大学的研究人员密切合作进行。

In this research the goal is to develop a nonparametric adaptive communications receiver strategy by exploiting results from the theory of universal classification and data compression. Analysis based upon the "typicality" of the data has become one of the primary theoretical and practical concepts in modern information theory. The so-called "Type" (appropriate histogram estimators of the amplitude distribution) have not only been shown to be sufficient statistics for both classification and compression, but have also been shown to converge exponentially fast to the true underlying distribution. Because type-based detectors make no a priori assumptions about the channel characteristics and measure the quantities needed to provide asymptotically optimal reception, these detectors can theoretically achieve the same exponential error rate as the clairvoyant receiver that knows the channel characteristics perfectly and uses them optimally. Measurements made during succeeding transmissions, possibly using the data transmissions themselves in a decision feedback paradigm, can be used to track channel variations. The approach will be extended to deal with intersample dependencies and colored noise by using channel measurements in an optimally effective way. Two techniques drawn from data compression work, context trees and Lempel-Ziv (universal) coding, will be examined to determine which represents channel-induced dependencies most efficiently and which is most adaptable. By merging systems based on these two theories, a receiver that adapts to unknown, time-varying channels will be developed. It will be demonstrated that this receiver can be used in multiuser channels, both wireless and optical fiber, with little modification. The research will develop the theoretical underpinnings of this adaptive receiver strategy, and will develop a complete software implementation of the receiver, using as test data actual communication channel recordings. This work will be performed by a close collaboration of researchers from Rice University and George Mason University.