基于Kaczmarz迭代的大规模MIMO系统低复杂度软输出信号检测  

Low-Complexity Soft-Output Signal Detection Based on Kaczmarz Method for Uplink Massive MIMO Systems

作　　者：申滨[1] 赵书锋 黄龙杨 SHEN Bin;ZHAO Shu-feng;HUANG Long-yang(Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Civil Aviation Flight University of China,Deyang,Sichuan 618300,China)

机构地区：[1]重庆邮电大学,重庆400065 [2]中国民用航空飞行学院,四川德阳618300

出　　处：《电子学报》2018年第11期2746-2752,共7页Acta Electronica Sinica

基　　金：国家科技重大专项基金(No.2016ZX03001010-004)

摘　　要：大规模MIMO系统上行链路中,最小均方误差(MMSE)算法能获得接近最优的线性检测性能,但是涉及复杂度较高的矩阵求逆运算.本文基于Kaczmarz迭代提出一种低复杂度软输出信号检测算法,在算法实现中避免了矩阵求逆运算,将实现复杂度由■(K^3)降为■(K^2).同时,引入了最优松弛参数进一步加快算法收敛,最后给出了两种用于信道译码的LLR的近似计算方法.仿真结果表明:所提出的Kaczmarz迭代软输出信号检测算法经过两到三次简单的迭代即可较快地收敛,并达到接近MMSE检测算法的误码率性能的水平,其性能与复杂度均优于基于矩阵近似求逆的一类检测算法.For massive MIMO system uplink,conventional minimum mean square error(MMSE)linear detection algorithm can achieve nearly optimal performance,but it involves complicated matrix inversion.A low-complexity detection algorithm based on Kaczmarz method is proposed in this paper,which can circumvent the matrix inverse operation and hence reduce the complexity from O(K 3)to O(K 2).Meanwhile,an optimal relaxation parameter is introduced to further accelerate the algorithm convergence,and two approximate methods of log-likelihood ratios(LLR)estimation for channel decoding are given as well.Simulation results verify that the proposed algorithm outperforms the Neumann series expansion algorithms on both bit error ratio(BER)and computational complexity.It converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.

关 键 词：大规模MIMO 低复杂度 Kaczmarz迭代 松弛参数 软输出 

分 类 号：TN929.5[电子电信—通信与信息系统]