Multi-dimensional matched filter identification technique for channel equalization deployed in spatial diversity receivers

Adem Coskun, I. Kale
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Abstract

This paper proposes a multi-dimensional matched filtering technique for spatial diversity receivers. The coefficients of the multi-dimensional matched filter are identified by making use of an adaptive filter, the update of which doesn't require the transmission of any training symbols within the transmitted data stream. Therefore the use of the proposed technique improves the data rate efficiency. Furthermore, it is well known that implementing multi-dimensional matched filtering is essential for equalization purposes to obtain the optimum error rate performance from spatial diversity receivers. For that reason the technique is designed not only to identify the unknown matched filter but also to simultaneously lead to the equalization of the channel too. In order to update the adaptive filter, the Constant Modulus Algorithm (CMA) is utilized, which is an implementation convenient algorithm. Therefore the proposed technique is not computationally complex in comparison to those identification algorithms proposed for spatial diversity receivers. Simulations are provided to present the equalization performance of the novel technique.
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用于空间分集接收机信道均衡的多维匹配滤波器识别技术
提出了一种空间分集接收机的多维匹配滤波技术。利用自适应滤波器识别多维匹配滤波器的系数,该滤波器的更新不需要在传输的数据流中传输任何训练符号。因此,采用该技术可以提高数据速率效率。此外,为了从空间分集接收机获得最佳误码率性能,实现多维匹配滤波是实现均衡的必要条件。因此,该技术不仅可以识别未知匹配滤波器,还可以同时实现信道的均衡。为了更新自适应滤波器,采用了一种实现方便的恒模算法(Constant Modulus Algorithm, CMA)。因此,与空间分集接收机的识别算法相比,该方法的计算复杂度较低。通过仿真验证了该方法的均衡性能。
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