基于概率裁剪的球形译码算法  

Sphere Decoding Detection Based on Probability-Distribution Node Pruning

作　　者：金鑫[1] 倪芸[1] 姚晓东[1] 

机构地区：[1]华东理工大学信息科学与工程学院,上海200237

出　　处：《华东理工大学学报（自然科学版）》2014年第3期371-375,共5页Journal of East China University of Science and Technology

摘　　要：在适当的裁剪函数下,基于概率裁剪的球形译码(SPSD)算法能有效逼近最大似然检测(ML)算法性能,但其复杂度在低信噪比下较高。本文重点对SPSD算法的复杂度进行优化,并提出改进算法。改进算法利用迫零检测(ZF)解计算出初始半径,能有效降低球形译码的搜索范围,并优化裁剪函数,在几乎不损失性能的前提下,有效降低算法复杂度。仿真结果表明,在多输入多输出(MIMO)系统中,改进算法能够逼近SPSD算法的性能,并有效减少算法复杂度,能很好地达到检测算法性能和复杂度之间的折中。Statistical pruning sphere decoder （SPSD） can effectively approximate the performance of maximum likelihood（ML） algorithm when using suitable pruning function, but its complexity is higher at low SNR. This paper focuses on lowering the complexity of SPSD and proposes an improved algorithm. In this algorithm, the initial radius, calculated by zero foreing（ZF） solution, can effectively reduce the search range and optimize the pruning function, which can lower the complexity effectively without losing performance. The simulation results show that for MIMO systems, the proposed algorithm can achieve similar performance to SPSD at low complexity such that the trade-off between the performance and complexity of algorithm can be obtained.

关 键 词：多输入多输出(MIMO) 球形译码(SD) 概率裁剪球形译码(SPSD) 迫零检测 (ZF) 裁剪函数 

分 类 号：TN911[电子电信—通信与信息系统]