摘要
提出了一种基于自组织神经网络的信道估计方法，可用于OFDM电力线通信系统的信道估计研究中．该方法可以将接收到的信号送给自组织神经网络，以实现对信道特性的连续自适应的估计，不需要预先知道电力线的信道特性便可以实现在限定的相位变化范围内，对信道传递函数的连续跟踪．通过对低压电力线信道环境的仿真，证明了该方法可以有效地应对信道的非线性效应．
In this paper, a self-organizing neural network method is proposed for channel estimation in Power- Line Communication （PLC） based on Orthogonal Frequency Division Multiplexing （OFDM）. In the proposed method, the received subcarrier-symbols are presented to a self-organizing neural network that adaptively finds the dusters of the QPSK constellation. This method does not require a priori knowledge 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 performances and that it is robust to nonlinearities.
出处
《哈尔滨理工大学学报》
CAS
北大核心
2009年第A01期47-51,共5页
Journal of Harbin University of Science and Technology
关键词
电力线通信
神经网络
信道估计
power-line communication
neural networks
channel estimation
