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Blind RBF equalizer for received signal constellation independent channel

机译:盲RBF均衡器,用于独立于接收信号星座的信道

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The purpose of this paper is to propose a novel cluster map based blind RBF equalizer for received signal constellation (RSC) independent channel. Without the channel estimator, firstly, a neural-gas algorithm is used to obtain the desired number of unlabeled RBF centers. Then these unlabeled centers are partitioned into appropriate subsets based on a cluster map generated from the known RBF equalizer structure. This process, which also can be viewed as the weight initialization, is implemented merely by several simple sorting operations. Finally, the weight is adjusted iteratively by a unsupervised least mean square (LMS) algorithm. Because of the effective weight initialization that comply with the underlying structure of the RBF equalizer, the proposed blind RBF equalizer achieves almost identical performance with the optimal RBF equalizer. The validity of the proposed equalizer is also demonstrated by computer simulations.
机译:本文的目的是提出一种基于新的基于集群地图的基于盲RBF均衡器,用于接收信号星座(RSC)独立信道。在没有信道估计器的情况下,首先,神经气体算法用于获得所需数量的未标记的RBF中心。然后,这些未标记的中心基于从已知的RBF均衡器结构生成的集群映射划分为适当的子集。该过程也可以被视为重量初始化,仅通过几个简单的分类操作来实现。最后,通过无监督的最小均方(LMS)算法迭代地调整重量。由于符合RBF均衡器的底层结构的有效权重初始化,所提出的盲RBF均衡器与最佳RBF均衡器实现了几乎相同的性能。计算机仿真也证明了所提出的均衡器的有效性。

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