基于迭代并行干扰消除的低复杂度大规模MIMO信号检测算法  

Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems

作　　者：申滨[1] 赵书锋[1] 金纯[1] SHEN Bin;ZHAO Shufeng;JIN Chun(Chongqing Key Laboratory of Mobile Communications,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学移动通信重点实验室,重庆400065

出　　处：《电子与信息学报》2018年第12期2970-2978,共9页Journal of Electronics & Information Technology

基　　金：重庆市科委重点产业共性关键技术创新专项(cstc2015zdcyztzx40008)~~

摘　　要：基于干扰消除思想该文提出一种适用于大规模MIMO系统上行链路的低复杂度迭代并行干扰消除算法,在算法实现中避免了线性检测算法所需的高复杂度矩阵求逆运算,将复杂度保持在。在此基础上,引入噪声预测机制,提出一种基于噪声预测的迭代并行干扰消除算法,进一步提高了硬判决检测性能。考虑天线间残留干扰,将干扰消除思想运用到软判决中,最后提出一种基于迭代并行干扰消除的低复杂度软输出信号检测算法。仿真结果表明:提出的信号检测方法的复杂度优于MMSE检测算法,经过几次简单的迭代,算法即快速收敛并获得接近甚至优于MMSE检测算法的误码率性能。Based on interference cancellation method, a low complexity Iterative Parallel Interference Cancellation （IPIC） algorithm is proposed for the uplink of massive MIMO systems. The proposed algorithm avoids the high complexity matrix inversion required by the linear detection algorithm, and hence the complexity is maintained only at （O（K2））. Meanwhile, the noise prediction mechanism is introduced and the noise-prediction aided iterative parallel interference cancellation algorithm is proposed to improve further the detection performance. Considering the residual inter-antenna interference, a low-complexity soft output signal detection algorithm is proposed as well. The simulation results show that the complexity of all the proposed signal detection methods are better than that of the MMSE detection algorithm. With only a small number of iterations, the proposed algorithm achieves its performance quite close to or even surpassing that of the MMSE algorithm.

关 键 词：大规模MIMO 低复杂度 迭代并行干扰消除 噪声预测 软输出 

分 类 号：TN929.5[电子电信—通信与信息系统]