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Second-order blind algorithms for adaptive recursive linear equalizers: Analysis and lattice implementation

机译：自适应递归线性均衡器的二阶盲算法：分析和晶格实现

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摘要

Adaptive recursive linear equalizers present important advantages in terms of performance and robustness compared to more standard finite impulse response structures, and provide a means for blindly initializing the decision feedback structure. We present an analysis of a pair of algorithms for the adaptation of the recursive part of the equalizer, which are based on the second-order statistics of the received signal, in a multichannel complex-valued setting with spatially coloured noise. When the number of equalizer poles is no less than the channel order, both algorithms enjoy a unique stationary point, which in addition is locally convergent; global convergence properties, on the other hand, can be quite different. When the optimum setting presents poles close to the stability boundary, the lattice structure is preferred for ease of stability monitoring. Lattice versions of the two algorithms are developed and their convergence properties discussed.
机译：与更标准的有限冲激响应结构相比，自适应递归线性均衡器在性能和鲁棒性方面显示出重要的优势，并提供了一种盲目初始化决策反馈结构的方法。我们介绍了在具有空间色噪声的多通道复数值设置中，基于接收信号的二阶统计量对均衡器的递归部分进行自适应的一对算法的分析。当均衡器极点的数量不小于信道阶数时，两种算法都具有唯一的固定点，此外，该固定点是局部收敛的。另一方面，全局收敛性可能会大不相同。当最佳设置的极点接近稳定边界时，为便于进行稳定性监视，最好使用晶格结构。开发了两种算法的格子版本，并讨论了它们的收敛特性。

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