Abstract: The antenna selection algorithm is the exhaustive search method. Its computational complexity grows rapidly as the number of antennas increases. It is quite impractical. Focusing on this problem, a fast antenna selection algorithm based on Sorenson similarity coefficient is proposed. It uses Sorenson similarity coefficient to express the correlation of two vectors, and selects the receive antennas with the largest norm and smallest similarity coefficient by searching the matrix row by row, so the system capacity can be increased most. Simulation results indicate that the capacity of the proposed algorithm is close to that of the optimal exhaustive search algorithm and its computational complexity is low in the case where the number of radio frequency chains is small.

Key words: Multiple Input Multiple Output(MIMO), antenna selection, channel capacity, Sorenson similarity coefficient

摘要： 穷举搜索天线选择算法的计算复杂度随天线的增多变大，影响实际应用。针对该问题，提出基于Sorenson相似系数的快速天线选择算法。利用Sorenson相似系数来表征信道矩阵行向量间的相关性，通过逐行递增的方法，选择相似系数最小且行范数最大的接收天线，从而最大程度地增加系统容量。仿真结果表明，该算法在射频链路较少时计算复杂度很低，且能获得接近最优算法的中断容量。

关键词: 多输入多输出, 天线选择, 信道容量, Sorenson相似系数

CLC Number: 

• TN92