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在大规模多输入多输出(MIMO)系统上行链路中,当基站端天线数远大于单天线用户数时,传统的最小均方误差(MMSE)检测算法能达到接近最优的线性信号检测性能.但是,MMSE算法涉及复杂的矩阵求逆,导致其难以快速有效地实现.为了平衡检测性能和计算复杂度之间的关系,对比分析了基于多项式展开的近似矩阵求逆方法和基于线性方程迭代求解的等效矩阵求逆方法,并将其应用于软判决检测中,充分利用了信道编译码的软信息,在降低检测算法复杂度的同时达到接近最优的检测性能.
In the uplink of large-scale multiple-input multiple-output (MIMO) system, the traditional minimum mean square error (MMSE) detection algorithm can achieve near optimal linear signal detection performance when the number of base station antennas is much larger than the number of single antenna users However, the MMSE algorithm involves complex matrix inversion, which makes it difficult to achieve fast and efficiently.In order to balance the relationship between detection performance and computational complexity, the approximate matrix inversion method based on polynomial expansion and linear equation iteration The equivalent matrix inversion method is applied to soft decision detection, making full use of the soft information of channel coding and decoding to achieve the near optimal detection performance while reducing the complexity of the detection algorithm.