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Recursive blind estimation and equalization of time-varying channel based parametric model

机译:基于时变信道的递归盲估计与均衡

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This paper proposes a new technique for recursive blind equalization of a time-varying IIR communication channel to obtain simultaneous estimation of channel impulse response and input symbols. The received sequences are represented as the output of a noisy non-Gaussian time-varying parametric model. A Pseudo Maximum Likelihood Estimation algorithm is proposed for the identification of channel parameters. The blind equalization is implemented by three algorithms: the recursive channel estimation algorithm, the Gaussian-mixture parameter estimation algorithm and the standard Kalman filtering algorithm. The equalization results are good even on low SNR received sequence and fast fading channel.
机译:本文提出了一种新技术,用于递归的IIR通信信道的递归盲均衡,以获得信道脉冲响应和输入符号的同时估计。接收的序列表示为嘈杂的非高斯时变参数模型的输出。提出了伪最大似然估计算法用于识别信道参数。盲均衡由三种算法实现:递归信道估计算法,高斯 - 混合参数估计算法和标准卡尔曼滤波算法。即使在低SNR接收的序列和快速衰落通道上,均衡结果也很好。

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