扩频系统降秩空时干扰抑制的联合迭代最小二乘算法
Reduced-Rank Space-Time Interference Suppression with Joint Iterative Least Squares Algorithms for Spread Spectrum Systems
摘要：
提出了一种新的基于参数向量联合迭代优化的自适应空时降秩干扰抑制最小二乘算法。建议的空时降秩方案包括一个联合迭代优化的投影矩阵，执行降维和自适应降秩参数向量，产生的符号估计。所提出的技术不需要奇异值分解（SVD），并自动找到降秩处理的最佳基集。我们提出了最小二乘（LS）表达式的投影矩阵和降秩参数向量的设计，我们进行的LS算法的收敛性能的分析。然后，我们开发递归最小二乘（RLS）自适应算法的计算效率的估计和算法自动调整的排名所提出的计划。的LS算法的凸性分析进行了发展的收敛性证明所提出的算法。对DS-CDMA系统空时干扰抑制应用的仿真结果表明，该方案在收敛性和跟踪性能上优于现有的降秩方案，且复杂度相当。
英文摘要：
This paper presents novel adaptive space-time reduced-rank interference suppression least squares algorithms based on joint iterative optimization of parameter vectors. The proposed space-time reduced-rank scheme consists of a joint iterative optimization of a projection matrix that performs dimensionality reduction and an adaptive reduced-rank parameter vector that yields the symbol estimates. The proposed techniques do not require singular value decomposition (SVD) and automatically find the best set of basis for reduced-rank processing. We present least squares (LS) expressions for the design of the projection matrix and the reduced-rank parameter vector and we conduct an analysis of the convergence properties of the LS algorithms. We then develop recursive least squares (RLS) adaptive algorithms for their computationally efficient estimation and an algorithm for automatically adjusting the rank of the proposed scheme. A convexity analysis of the LS algorithms is carried out along with the development of a proof of convergence for the proposed algorithms. Simulations for a space-time interference suppression application with a DS-CDMA system show that the proposed scheme outperforms in convergence and tracking the state-of-the-art reduced-rank schemes at a comparable complexity.
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