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Interference rejection using the time-dependent constant modulus algorithm (CMA) and the hybrid CMA/spectral correlation discriminator

机译:使用时变常数模量算法(CMA)和混合CMA /频谱相关鉴别器的干扰抑制

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摘要

Two new blind adaptive filtering algorithms for interference rejection using time-dependent filtering structures are presented. The time-dependent structure allows the adaptive filter to outperform the conventional adaptive filter implemented with a time-independent structure for filtering of cyclostationary communication signals. At the same time, the blind adaption algorithms allow the filters to operate without the use of an external training signal. The first algorithm applies the CMA to an unconstrained time-dependent filtering structure. The second algorithm applies the CMA to a spectral correlation discriminator, which is constrained to select signals with unique spectral correlation characteristics. Using computer simulations, it is shown that the blind time-dependent filtering algorithms can provide mean-square errors (MSEs) and bit error rates (BERs) that are significantly lower than the MSEs and BERs provided using conventional time-independent adaptive filters. It is also shown that these processors can outperform the nonblind training-sequence directed time-independent adaptive filter.
机译:提出了两种新的基于时变滤波结构的抗干扰盲自适应滤波算法。时间相关的结构允许自适应滤波器优于传统的自适应时间滤波器,传统的自适应滤波器采用与时间无关的结构来滤波循环平稳通信信号。同时,盲自适应算法允许滤波器在不使用外部训练信号的情况下运行。第一种算法将CMA应用于不受时间限制的滤波结构。第二种算法将CMA应用于频谱相关鉴别器,后者被约束为选择具有独特频谱相关特性的信号。使用计算机仿真显示,与时间无关的盲滤波算法可以提供均方差(MSE)和误码率(BER),这些均方差和误码率(BER)明显低于使用传统的与时间无关的自适应滤波器提供的MSE和BER。还表明,这些处理器的性能优于非盲训练序列定向的时间无关自适应滤波器。

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