基于MUSIC和ML方法的MIMO系统参数估计

该文提出了一种基于MUSIC和ML方法联合估计MIMO系统频偏和信道增益的算法，该算法首先使用MUSIC方法估计出多个发射天线到某一接收天线的频偏子集，然后利用最大似然方法在这个有限子集中分离出不同天线对之间的频偏，最后在频率同步的基础上利用最大似然估计器对信道增益进行估计。该算法解决了在估计多个频偏时直接使用最大似然估计进行多维搜索的问题，将多维搜索转化为一维搜索，降低了算法的复杂度。

Parameter Estimation for MIMO System Based on MUSIC and ML Methods

The frequency offsets and channel gains estimation problem for MIMO system in the case of flat-fading channels is addressed. Based on the MUSIC (Multiple Signal Classification) and the ML (Maximum Likelihood) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. Then all frequency offsets in the subset are identified with the ML method. Finally channel gains are estimated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of the joint ML estimation, which is essentially a multi-dimensional search scheme.