基于参数模型的时变信道递归盲估计与均衡

Zheng Yuanjin
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引用次数: 2

摘要

本文提出了一种时变IIR通信信道的递归盲均衡新技术,以同时估计信道的脉冲响应和输入符号。接收到的序列表示为一个有噪声的非高斯时变参数模型的输出。提出了一种用于信道参数识别的伪极大似然估计算法。盲均衡通过三种算法实现: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。即使在低信噪比接收序列和快速衰落信道下,均衡效果也很好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recursive blind estimation and equalization of time-varying channel based on parametric model
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.
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