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

摘要为快速变化的多址通信环境而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）数据支持下具有优越性能的系统自适应性。自适应短数据记录设计是一个成熟学科的自然下一步，它已经广泛地解决了前两个(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属性）。基于短数据记录的系统自适应对于开发实用的自适应接收机是必要的，当它们在快速变化的通信环境中运行时，表现出优越的信噪比（SINR）或误码率（BER）性能，这些环境极大地限制了可用于自适应和重新设计的输入数据支持。在这个项目中，一个新的研究方向被确定和追求，它是估计理论、通信理论和均方最佳线性滤波的多学科交叉。考虑在存在多用户或其他形式的严重干扰的情况下恢复任意输入信号矢量空间和给定的信息承载信号矢量。成功解决短数据记录下自适应接收机设计问题的关键是采用具有不同偏差/方差特征的接收机估计器，并以数据为中心的方式有效地控制这些特征。在这个项目中，研究人员开发了一个短数据记录自适应过滤框架，该框架涉及(i)用于生成具有不同偏差/方差权衡的过滤器估计器序列的工具，以及（ii）用于在给定输入数据记录的序列中选择最合适的估计器的工具。辅助向量（AV）滤波方法是研究人员在过去几年开发的，是解决短数据记录自适应滤波问题的最先进的实际工程解决方案，被用作基准案例研究。这种研究框架的理论和实践意义是深远的。提供对偏差/方差平衡的完全控制的有偏估计器和算法很少在文献中报道，如果在通信应用环境中有的话。虽然这项工作的目标应用都是关键的通信问题，但相关的理论发展可能会触及多学科工程的许多方面，这些方面受到“维度诅咒”的阻碍，并且可以通过有限的输入数据从自适应滤波和/或自适应系统优化中受益。

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.