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Design of a Blind Spatial and Temporal RBF Equalizer Using a Genetic Algorithm

机译:基于遗传算法的盲时空RBF均衡器设计

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This paper describes a new solution to channel in-tersymbol interference and nonlinear distortion by means of an adaptive array antenna and radial basis function (RBF) equalizer. The RBF equalizer can reduce the influence of intersymbol interference and additive noise in the digital communication system. It is also well known to eliminate nonlinear distortion effectively. However, conventional RBF equalizers including our previous proposed equalizer, a spatial and temporal RBF equalizer using adaptive array antenna, need training data to learn channel states, which incurs a decline in the data rate. In this paper, without training data, we construct a blind spatial and temporal RBF equalizer using genetic algorithm. We also describe a method of synthesizing Bayesian decision variables of RBF equalizers in order to obtain better performance. The RBF equalizer based on the proposed method can achieve a remarkable improvement in BER characteristics and its performance is demonstrated by computer simulations.
机译:本文介绍了一种通过自适应阵列天线和径向基函数(RBF)均衡器解决信道间干扰和非线性失真的新方法。 RBF均衡器可以减少数字通信系统中符号间干扰和附加噪声的影响。有效消除非线性失真也是众所周知的。然而,包括我们先前提出的均衡器,使用自适应阵列天线的空间和时间RBF均衡器在内的常规RBF均衡器需要训练数据来学习信道状态,这会导致数据速率下降。在没有训练数据的情况下,我们使用遗传算法构造了一个盲时空RBF均衡器。我们还描述了一种合成RBF均衡器的贝叶斯决策变量的方法,以获得更好的性能。基于该方法的RBF均衡器可以显着改善BER特性,并通过计算机仿真证明了其性能。

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