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REDUCED-COMPLEXITY MULTI-STAGE BLIND CLUSTERING EQUALISER

机译:降低复杂度的多阶段盲簇均衡器

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摘要

A multi-stage blind clustering algorithm is proposed for equallsadon of M-QAM channels.A novel hierarchical decomposition divides the overall task of equalising a highorder QAM channel into much simpler sub-tasks.Each subtask can be accomplished fast and reliably using a blind clustering algorithm derived originally for 4-QAM signals.The well-known constant modulus algorithm(CMA)is used as a benchmark to assess this novel multi-stage blind equaliser and it is demonstrated that the new blind adaptive algorithm.achieves much faster convergence.This multi-stage clustering cqualiset only requires slightry more computations than the very simple CMA and,like the latter.its computational complexity does not increase as the levels of digital symbols increase.
机译:提出了一种针对M-QAM信道均衡的多阶段盲聚类算法,通过新颖的层次分解将均衡高阶QAM信道的总体任务划分为更简单的子任务,通过盲聚可以快速,可靠地完成每个子任务。该算法最初是为4-QAM信号而派生的。众所周知的恒模算法(CMA)被用作评估该新型多级盲均衡器的基准,并证明了该新型盲自适应算法实现了更快的收敛速度。与非常简单的CMA相比,多阶段聚类算法仅需要稍微多的计算,并且像后者一样。其计算复杂度不会随着数字符号级别的增加而增加。

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