基于Kalman滤波器的放大转发双向中继联合信道估计方法

针对遵从放大转发协议的双向中继网络的联合信道估计问题，提出了一种基于Kalman滤波器的新方法。首先根据联合信道构成特点将其划分为自干扰部分及传输部分，通过AR模型对这两部分自相关函数进行近似化处理，建立了联合信道时变过程的状态方程，结合接收的训练序列信号，给出了具有Kalman滤波器形式的估计方法。随后在证明了该方法的一致收敛性质的同时，列出了误差性能限所满足的Riccati方程表达式。仿真结果表明，新估计方法相比于最大似然方法在均方误差方面具有明显的性能优势。

A Cascade Channel Estimator of Amplify-and-Forward Two-Way Relay Networks Based on Kalman Filter

This paper deals with cascade channel estimation of Amplify-and-Forward (AF) two-way relay networks (TWRN), and a new estimator is proposed based on Kalman filter. Firstly, cascade channel of AF TWRN is divided into self-interference part and transmission part functionally. Then, auto-correlation functions of these two parts (ACF) are approximated by auto-regressive (AR) model to obtain Gauss-Markov process of the channel, and the resultant Kalman estimator is deduced according on received training signals. After the property of convergence is proved, the bound of mean square error (MSE) is also derived in the form of Riccati equation. The final numeral simulation demonstrates that the new estimator outperforms its maximum likelihood (ML) counterpart in the merit of MSE.