ITR: Development of a Novel Short-Data-Record Adaptive Filtering Framework for Rapidly Changing Communications Environments

PI：S. N. Batalama和D. A.为快速变化的多址通信环境设计的接收机的有效性取决于以下设计属性：（i）低计算复杂度，（ii）抗多址干扰，以及（iii）在有限（短）数据支持下具有上级性能的系统自适应性。自适应短数据记录设计似乎是成熟学科的自然下一步，该学科已广泛解决了前两个，（i）和（ii），理想设置中的设计目标（完全已知或渐近估计的统计特性）。基于短数据记录的系统自适应性是开发具有上级信干噪比（SINR）或误码率（BER）的实用自适应接收机所必需的当它们在快速变化的通信环境中运行时，这些环境大大限制了可用于适应和重新设计的输入数据支持。估计理论、通信理论和均方最优线性滤波的多学科交叉。考虑任意输入信号矢量空间和给定的信息承载信号矢量，在存在多用户或其他形式的严重干扰的情况下恢复。短数据记录下自适应接收机设计问题成功解决的关键是采用具有变化的偏差/方差特性的接收机估计器，并以数据为中心的方式有效地控制这些特性。在这个项目中，研究人员开发了一个短数据记录自适应滤波框架，包括（i）用于生成具有不同偏差/方差权衡的滤波估计序列的工具，以及（ii）用于为给定的输入数据记录选择序列中最合适的估计量的工具。在过去的几年中，作为一个国家的最先进的实际工程解决方案的短数据记录自适应滤波的问题的研究人员开发的矢量（AV）滤波手段被用作基准案例研究。 这样一个研究框架的理论和实践意义是深远的。有偏估计和算法，提供完全控制的偏差/方差平衡很少在文献中报道，如果有的话，在通信适用的上下文中。虽然这项工作的目标应用都是criticalcommunications问题，相关的理论发展可能会触及许多方面的多学科工程，阻碍了“灾难的维度”，并可能受益于自适应滤波和/或自适应系统优化通过有限的输入数据。

PIs: S. N. Batalama and D. A. PadosPROJECT ABSTRACTThe effectiveness of a receiver designed for a rapidly changing multiple access communications environment depends on the following design attributes: (i) low computational complexity, (ii) multiple-access-interference resistance, and (iii) system adaptivity with superior performance under limited (short) data support. Adaptive short-data-record designs appear as the natural next step for a matured discipline that has extensively addressed the first two, (i) and (ii), design objectives in ideal setups (perfectly known or asymptotically estimated statistical properties). System adaptivity based on short data records is necessary for the development of practical adaptive receivers that exhibit superior signal-to-interference-plus-noise ratio (SINR) or bit-error-rate (BER) performance when they operate in rapidly changing communications environments that limit substantially the input data support that is available for adaptation and redesign.A novel line of research is identified and pursued in this project that lies in a multidisciplinary intersection of Estimation Theory, Communications Theory, and Mean-Square optimum linear filtering. Consider an arbitrary input signal vector space and a given information bearing signal vector to be recovered in the presence of multiuser or other forms of heavy interference. A key for the successful solution to the problem of adaptive receiver design under short data records is to employ receiver estimators with varying bias/variance characteristics and to control effectively these characteristics in a data-centric manner. In this project, the investigators develop a short-data-record adaptive filtering framework that involves (i) the tools for the generationof a sequence of filter estimators with varying bias/variance tradeoff, as well as (ii) the tools for selecting the most appropriate estimator in the sequence for a given input datarecord. The Auxiliary-Vector (AV) filtering means developed by the investigators during the past few years as a state-of-the-art practical engineering solution to the problem of short-data-record adaptive filtering is used as a benchmark case-study. The theoretical and practical implications of such a research framework are far reaching. Biased estimators and algorithms thatoffer full control over the bias/variance balance are rarely reported in the literature, if any in a communications applicable context. While the target applications of this work are all criticalcommunications problems, the pertinent theoretical developments may touch many aspects of multidisciplinary engineering that are hampered by the ``curse of dimensionality'' and could benefit from adaptive filtering and/or adaptive system optimization through limited input data.