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大规模MIMO系统中的一种自适应SIC检测算法
马敏,宋云超
0
(南京信息职业技术学院 通信学院,南京 210023;南京邮电大学 电子科学与工程学院,南京 210023)
摘要:
与传统系统相比,大规模多入多出(MIMO)系统能更加有效地提高频谱效率。利用传统的最小均方误差(MMSE)信号检测算法求解大规模MIMO系统,虽然检测结果接近最优,但是矩阵的求逆运算导致计算的复杂度非常高。提出了一种自适应排序干扰消除(SIC)检测算法,在逐次超松弛(SOR)迭代运算的基础上,通过干扰消除降低待检测矩阵的维度。通过仿真分析,得出所提算法的复杂度低于Jacobi、SOR检测算法,且在迭代次数较少的情况下,算法的误码率(BER)性能明显优于SOR检测算法。
关键词:  大规模MIMO  自适应SIC检测  低复杂度
DOI:
基金项目:国家自然科学基金资助项目(61372126);江苏高校品牌专业建设工程资助项目(PPZY2015A092);江苏高校“青蓝工程”优秀教学团队资助项目(2017)
An adaptive SIC detection algorithm in large-scale MIMO systems
MA Min,SONG Yunchao
(School of Telecommunications,Nanjing College of Information Technology,Nanjing 210023,China;School of Electronic Science and Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
Abstract:
Compared with traditional Multiple-Input Multiple-Output(MIMO) systems,large-scale MIMO systems have larger spectrum efficiency.Although the traditional minimum mean square error(MMSE) detection algorithm has nearly optimal bit error rate(BER) performance in large-scale MIMO detections,its computational complexity is very high due to the inverse calculation of the large dimensional matrix.This paper proposes an adaptive sorting interference cancellation(SIC) detection algorithm which is based on the successive over relaxation(SOR) iterative operation,and the dimension of the detection matrix in each iteration is reduced using interference cancellation.Simulation analysis shows that the complexity of this algorithm is lower than that of Jacobi,SOR detection algorithm,and the BER performance of this algorithm is better than that of SOR algorithm.
Key words:  large-scale MIMO  adaptive SIC detection  low-complexity
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