Minimum mean squared error equalization using A priori information
Minimum mean squared error equalization using A priori information
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DOI：
10.1109/78.984761
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发表时间：
2002-03-01
影响因子：
5.4
通讯作者：
Koetter, R
中科院分区：
文献类型：
--
作者：
Tüchler, M;Singer, AC;Koetter, R
在码间干扰（ISI）信道上传输的数据的联合均衡和解码领域已经取得了许多重要进展。Turbo均衡是解决这个问题的迭代方法，其中最大后验概率（MAP）均衡器和MAP解码器在所发送的符号上以先验概率的形式交换软信息。最近已经引入了许多用于Turbo均衡的降低复杂度的方法，其中MAP均衡被次优的低复杂度方法取代。在本文中，我们探讨了一些低复杂度的软输入/软输出（SISO）均衡算法的最小均方误差（MMSE）标准的基础上。这包括扩展现有的方法，一般信号星座和推导出一种新的方法，需要更低的复杂性比MMSE最优的解决方案。所有的方法进行了定性分析，通过观察均衡的数据序列的均方误差平均。我们表明，对于Turbo均衡应用，基于MMSE的SISO均衡器相比MAP均衡器表现良好，同时提供了一个巨大的复杂度降低。
A number of important advances have been made in the area of joint equalization and decoding of data transmitted over intersymbol interference (ISI) channels. Turbo equalization is an iterative approach to this problem, in which a maximum a posteriori probability (MAP) equalizer and a MAP decoder exchange soft information in the form of prior probabilities over the transmitted symbols. A number of reduced-complexity methods for turbo equalization have recently been introduced in which MAP equalization is replaced with suboptimal, low-complexity approaches. In this paper, we explore a number of low-complexity soft-input/soft-output (SISO) equalization algorithms base on the minimum mean square error (MMSE) criterion. This includes the extension of existing approaches to general signal constellations and the derivation of a novel approach requiring less complexity than the MMSE-optimal solution. All approaches are qualitatively analyzed by observing the mean-square error averaged over a sequence of equalized data. We show that for the turbo equalization application, the MMSE-based SISO equalizers perform well compared with a MAP equalizer while providing a tremendous complexity reduction.