大规模MIMO下具有反馈的低复杂度检测算法

Low complexity detection algorithm with feedback in massive MIMO

针对大规模MIMO系统,信号检测算法的复杂度往往呈指数级增长的问题,通过对传统的QRD-M检测算法和树搜索的深度研究,对其进行改进,得出一种具有反馈的低复杂度检测算法,该算法主要运用分支的权重和分支间的反馈对树进行修剪,然后运用树搜索的原理进行搜索输出。仿真结果表明,该改进算法以降低较少系统性能的代价,能够极大地降低计算复杂度,是一种折衷的高效检测算法,完全能运用于大规模MIMO系统中。

For massive MIMO, there is an exponential growth problem on the complexity of the signal detection algorithms. Based on the depth research on the conventional QRD-M detection algorithm and tree search, a low complexity detection algorithm with feedback is proposed in this paper, which mainly uses the branch weights and feedbacks in branchs to trim tree, and then uses the principles of tree search to output the result. Through complexity analysis and numerical simulations, it is proved that the proposed algorithm can greatly reduce the computational complexity and does not excessively degrade system performance. Therefore, the proposed algorithm is a eclectic efficient detection algorithm and can he also entirely used to the massive MIMO.