快时变OFDM信道下的信道跟踪

基于信道相关矩阵的信号子空间的缓慢变化,把信道估计转化为一个无约束的最小化问题。为了解决这个无约束的最小化问题,引进了著名的基于卡尔曼滤波的子空间追踪方法。该算法利用恒定的信号子空间构造状态方程和观测方程,然后通过迭代来求解一个最优值。仿真实验结果显示基于卡尔曼滤波的信道估计方法能很好的追踪快时变信道,在出现较大多普勒频移时表现出优异性能。

Channel Tracking of Fast Fading OFDM Channels

Considering the slow variations of the channel correlation matrix＇s signal subspace, we first translate the estimation of channel parameters into an unconstrained minimization problem. Then, to solve this minimization problem, a novel Kalman-filter based subspace tracking method is proposed, which employs the constant signal subspace to construct state equation and measurement equation, and then solve the optimal value through iteration. It is shown that the proposed Kalman filter method is able to effectively track the time-varying channels, and exhibits better performance with larger Doppler frequency spread.