一种低复杂度近最佳的MIMO信号检测算法  

MIMO signal detection algorithm with low-complexity and near-optimal-performance

作　　者：刘金铸[1] 薛婷[2] 

机构地区：[1]南京信息工程大学电子与信息工程学院,南京210044 [2]南京信息工程大学信息与控制学院,南京210044

出　　处：《南京信息工程大学学报（自然科学版）》2013年第2期167-170,共4页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：江苏省工业支撑计划(BE2011195)

摘　　要：在多输入多输出(MIMO)系统的信号检测算法中,最大似然(ML)算法具有最佳检测性能,但因其复杂度随天线数及调制阶数的增加呈指数增加而不实用.排序干扰逐次消去的最小均方误差(MMSE-OSIC)算法具有很低的复杂度,但因迭代检测过程中的差错传播使得检测性能与最佳检测相比有很大差距.针对以上算法的缺点,提出了一种低复杂度近最佳的MIMO信号检测算法,该算法对MMSE-OSIC算法的检测顺序进行调整,首先通过比较信道逆矩阵行向量的范数确定最弱信号层,对该发射信号的所有可能值进行遍历搜索,在保证最弱信号层尽可能正确检测的前提下,对剩余信号层采用MMSE-OSIC算法检测.理论分析及仿真结果表明,该算法有效抑制了迭代检测过程中的差错传播,几乎达到了最佳检测性能,同时具有较低的复杂度,在检测性能与复杂度之间给出了很好的折衷.In the signal detection algorithms for multiple input multiple output （MIMO） system, maximum likeli- hood （ML） detection offers the optimal performance while it encounters difficulties in practical system because of its computational complexity, which is increased exponentially with the number of antennas and modulation order. Minimum mean square error-ordered successive interference cancellation （MMSE-OSIC） algorithm has low com- plexity, but comparing with the optimal detection, its detection performance has a substantial margin due to error propagation in the progress of iterative detection. For dealing with the above algorithms＇ shortcoming, a new detection algorithm with low-complexity and near-optimal-performance is proposed. The algorithm makes readjustments of de- coding order in MMSE-OSIC algorithm, which begins with the determination of the weakest emission signal layer by comparing the maximum norm of row vectors,then makes exhaustive search on this transmitted signal; on the prem- ise of the correct detection of weakest signal as possible,MMSE-OSIC algorithm is used for the detection of the re- maining signal layers. Theoretic analysis and simulation results show that the algorithm can effectively strain error propagation in the progress of iterative detection and nearly reach optimal performance at low computational com- plexity. An appropriate trade-off between detection performance and computation complexity is obtained by this im- proved algorithm.

关 键 词：多输入多输出 干扰逐次消去 最小均方误差 最大似然 检测顺序 

分 类 号：TN911.7[电子电信—通信与信息系统]