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arXiv 1301.2697cs.ITmath.IT
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基于交替优化设计的多天线系统自适应降秩均衡算法

Adaptive Reduced-Rank Equalization Algorithms Based on Alternating Optimization Design Techniques for Multi-Antenna Systems

Rodrigo C. de Lamare, Raimundo Sampaio-Neto

摘要:

针对MIMO空间复用系统,提出了一种新的基于交替优化设计技术的自适应降秩多输入多输出(MIMO)均衡方案和算法。所提出的降秩均衡结构由两个均衡阶段的联合迭代优化组成,即,执行降维的变换矩阵和检索所需传输符号的降秩估计器。所提出的降秩架构被纳入均衡结构,允许判决反馈和线性方案,以减轻天线间和符号间干扰。我们开发交替最小二乘(LS)表达式的变换矩阵和降秩估计的设计以及计算效率高的交替递归最小二乘(RLS)自适应估计算法。然后,我们提出了一个算法,自动调整所提出的计划的模型阶数。最小二乘算法的分析进行了收敛的充分条件和证明所提出的算法的收敛性降秩维纳滤波器。仿真结果表明,所提出的均衡算法优于现有的降秩和满秩算法,而需要相当的计算成本。

英文摘要:

This paper presents a novel adaptive reduced-rank {multi-input multi-output} (MIMO) equalization scheme and algorithms based on alternating optimization design techniques for MIMO spatial multiplexing systems. The proposed reduced-rank equalization structure consists of a joint iterative optimization of two equalization stages, namely, a transformation matrix that performs dimensionality reduction and a reduced-rank estimator that retrieves the desired transmitted symbol. The proposed reduced-rank architecture is incorporated into an equalization structure that allows both decision feedback and linear schemes for mitigating the inter-antenna and inter-symbol interference. We develop alternating least squares (LS) expressions for the design of the transformation matrix and the reduced-rank estimator along with computationally efficient alternating recursive least squares (RLS) adaptive estimation algorithms. We then present an algorithm for automatically adjusting the model order of the proposed scheme. An analysis of the LS algorithms is carried out along with sufficient conditions for convergence and a proof of convergence of the proposed algorithms to the reduced-rank Wiener filter. Simulations show that the proposed equalization algorithms outperform the existing reduced-rank and full-rank algorithms, while requiring a comparable computational cost.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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