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Power-line communications channel estimation and tracking by a competitive neural network

机译:电力线通信信道的竞争神经网络估计和跟踪

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摘要

In this paper, a decision-directed method is proposed for channel estimation and equalization in power-line communication (PLC) based on orthogonal frequency-division multiplexing (OFDM). In the DDE (decision-directed estimation) method proposed, the received subcarrier-symbols are presented to a competitive neural network that adaptively finds the clusters of the QAM (quadrature amplitude modulation) constellation. This method does not require a priori know/edge on the powerline then allowing a blind estimation of the channel with tracking capabilities limited by constraints on the phase changes. Simulations on a realistic indoor power-line system show that the proposed method achieves very good channel estimation and equalization performances and that it is robust to impulsive noise and nonlinearities
机译:本文提出了一种基于正交频分复用(OFDM)的电力线通信(PLC)信道估计和均衡的决策导向方法。在提出的DDE(决策导向估计)方法中,将接收到的子载波符号呈现给竞争性神经网络,该网络自适应地找到QAM(正交幅度调制)星座图的簇。该方法不需要电力线上的先验知识/边缘,然后允许对信道进行盲估计,并且跟踪能力受相位变化的限制。在现实的室内电力线系统上进行的仿真表明,该方法具有很好的信道估计和均衡性能,并且对脉冲噪声和非线性具有鲁棒性。

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