Undermodeled equalization: a characterization of stationary points for a family of blind criteria
Undermodeled equalization: a characterization of stationary points for a family of blind criteria
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欠模型均衡：一系列盲准则的驻点表征
DOI：
10.1109/78.747781
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
P. Regalia
中科院分区：
文献类型：
--
作者：
P. Regalia
我们攻击的具体问题，均衡器的性能在欠模的情况下，完美的均衡性的假设被驳回，有利于一个更现实的情况下，没有均衡器的设置可以实现完美的信道均衡。我们推导出一个家庭的盲目标准，呼吁，默许或有意，最大限度地提高组合信道均衡器脉冲响应的不同序列规范的比率候选收敛点的表征。这可以在实际实现中通过使用不同阶数的均衡器输出累积量来实现。流行的戈达尔和沙尔维-温斯坦方案被容纳在标准族的一个极端。我们还表明，每个最大值在另一个极端的家庭，涉及逐步高阶输出累积量，产量，准确地说，一个维纳响应。这表明，使用逐步高阶统计量的盲算法可能比使用更适度的阶统计量的盲算法更接近维纳响应。此外，我们表明，超指数家族的算法也包括在内，并建立一个收敛证明欠模的情况下，呼吁没有近似。最后，一些显然新颖的界限可达到的开眼措施在欠模的情况下也得来。
We attack specific problems related to equalizer performance in undermodeled cases in which assumptions of perfect equalizability are dismissed in favor of a more realistic situation in which no equalizer setting may achieve perfect channel equalization. We derive a characterization of candidate convergent points for a family of blind criteria which appeal, tacitly or wittingly, to maximizing the ratio of different sequence norms of the combined channel-equalizer impulse response. This may be accomplished in a practical implementation by using equalizer output cumulants of different orders. The popular Godard and Shalvi-Weinstein schemes are accommodated at one extreme of the family of criteria. We also show that each maximum at the other extreme of the family, involving progressively higher order output cumulants, yields, precisely, a Wiener response. This suggests that blind algorithms using progressively higher order statistics may converge more closely to a Wiener response than those using more modest order statistics. We show, moreover, that the superexponential family of algorithms is also included and establish a convergence proof for undermodeled cases that appeals to no approximation. Finally, some apparently novel bounds on attainable open-eye measures in undermodeled cases are also derived.