多输入多输出系统中基于多级维纳滤波的均衡算法

基于多级维纳滤波器,提出了一种多输入多输出系统中的降秩自适应均衡算法.该算法利用多级维纳滤波器得到一组子空间基向量,通过子空间投影,把均衡器输出限定在低维子空间内,从而降低了自适应均衡的迭代复杂度,加快了收敛速度.理论分析和仿真表明,降秩均衡算法有效地提高了均衡器的收敛速度,降低了计算复杂度,并在多级维纳滤波器的级数不超过 10 的情况下,就能达到近似满秩均方误差性能.

Adaptive Reduced-Rank Linear Equalization of Multiple Input Multiple Output Frequency Selective Channels Based on Multistage Wiener Filter

Based on multistage Wiener filter,an reduced-rank adaptive equalizer for multiple input multiple output systems was proposed.The proposed algorithm uses the multistage Wiener filter to compute the base vectors of a subspace,and the output of the equalizer is then restricted in the lower-dimensional subspace by projecting input vectors into the subspace.Thus,the computational complexity is reduced and the convergence rate is increased.Theoretical analysis and simulation results show that the convergence rate of the proposed method is significantly faster and the computational complexity is much lower than existing adaptive algorithms.The proposed algorithm can achieve near full-rank mean square error performance with filter rank no more than 10.