Joint Space-Time Auxiliary-Vector Filtering for DS/CDMA Systems with Antenna Arrays

研究了数据样本支持有限的高维矢量空间中的盲自适应滤波问题。重点研究了具有天线阵列的DS/CDMA通信系统的联合空时自适应处理。目标是开发快速，低复杂性的优化程序，在小数据支持情况下表现出优越的干扰（多址干扰和信道噪声）抑制特性。低优化复杂度目标意味着矩阵反演和/或特征分解操作是非常不可取的。在这种情况下，本研究的核心主题是开发和分析归纳的条件优化程序，其形式是加权辅助向量序列，它们彼此正交，并与感兴趣的联合时空向量方向正交。

We consider the problem of blind adaptive filtering in high- dimension vector spaces with limited data sample support. The focus application is joint space-time adaptive processing for DS/CDMA communications systems with antenna arrays. The objective is the development of fast, low complexity optimization procedures that exhibit superior disturbance (multiple-access- interference and channel noise) suppression characteristics in small data support situations. The low optimization complexity objective implies that matrix inversion and/or eigen decomposition operations are highly undesirable. In this context, the core subject of this investigation is the development and analysis of inductive, conditional optimization procedures in the form of a sequence of weighted auxiliary vectors that are orthonormal to each other and to the joint space-time vector direction of interest.