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

研究了高维向量空间中有限数据样本支持下的盲自适应滤波问题.重点应用于具有天线阵列的DS/CDMA通信系统的联合空时自适应处理。 我们的目标是开发快速，低复杂度的优化程序，表现出上级干扰（多址干扰和信道噪声）的抑制特性，在小数据支持的情况下。低优化复杂度目标意味着矩阵求逆和/或本征分解操作是非常不期望的。在这种情况下，本次调查的核心主题是归纳的，有条件的优化程序的形式是一个序列的加权辅助向量，正交相互和联合时空向量的方向感兴趣的发展和分析。

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.