一种基于分数采样的混合盲均衡算法仿真研究

A Kind of Novel Blind Equalization Algorithm Based on Fractional Sampling Method

在数字通信中,盲均衡是克服多径衰落信道导致的码间干扰的一种有效方法。超指数盲均衡算法的迭代算法收敛速度快,且便于跟踪时变信道。同时由于实际信道往往为非最小相位系统,此时线性均衡器性能不佳。因此针对严重频率衰落和非线性相位失真信道,提出了一种分数采样的混合盲均衡算法,并获得了较快的收敛速度和较小的剩余均方误差。仿真结果证明了该算法的有效性。

Blind equalization is an effective way to suppress the inter-symbol interference （ISI）, which is caused by multipath fading communication channels, The super-exponential iteration （SEI） blind equalization algorithm has the advantage of good tracking capability of the time varying channel. However real channels are generally non-minimum phase systems, baud-spaced equalizers exhibit poor performance under this circumstance. Based on fractional sampling method, a new super-exponential iteration decision feedback blind equalization algorithm for severely nonlinear phase distortion channels was proposed. The simulation results show that the proposed algorithm with faster convergence rate acquires an improvement of about 7dB reduction in residual MSE as comparing with the MSE obtainable with the baud-spaced one.