Channel estimation for OFDM systems using adaptive radial basis function networks
Channel estimation for OFDM systems using adaptive radial basis function networks
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DOI：
10.1109/tvt.2002.800619
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发表时间：
2003-04
期刊：
影响因子：
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通讯作者：
Xiaobo Zhou;Xiaodong Wang-
中科院分区：
文献类型：
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作者：
Xiaobo Zhou;Xiaodong Wang-
在多径衰落信道下，提出了一种新的基于导频符号辅助的信道估计方法，该方法不需要知道信道的统计信息(如多普勒或功率谱)。它基于径向基函数(RBF)网络对衰落过程的动力学建模。提出了一维径向基函数神经网络和二维径向基函数神经网络来利用时频域和时频域中的信道相关性。所提出的径向基函数神经网络本质上是导频信道的非线性插值器。与已有的基于线性滤波的OFDM信道估计方法相比，新方法不仅对衰落速率具有较强的鲁棒性，而且在相对较快的衰落信道中表现出更好的性能。
We propose a new scheme for pilot-symbol-aided channel estimation in orthogonal frequency-division multiplexing (OFDM) systems in multipath fading channels, that does not require knowledge of the channel statistics (e.g., Doppler or power spectrum). It is based on using the radial basis function (RBF) network to model the dynamics of the fading process. Both one-dimensional and two-dimensional RBF networks are proposed to exploit the channel correlation in the time domain and in the time-frequency domain. The proposed RBF networks are essentially nonlinear interpolators of the pilot channels. Compared with the existing OFDM channel estimation methods based on linear filtering, the proposed new techniques offer both robustness to fading rate, and a better performance especially in relatively fast fading channels.