Wu Hebiao, Shen Bin, Zhao Shufeng, Gong Peng
Chongqing Key Laboratory of Mobile Communications Technology, School of Communication and Information Engineering (SCIE), Chongqing University of Posts and Telecommunications (CQUPT), 400065 Chongqing, China.
National Key Laboratory of Mechatronical Engineering and Control, School of Mechatronical Engineering, Beijing Institute of Technology (BIT), 100081 Beijing, China.
Sensors (Basel). 2020 Mar 11;20(6):1564. doi: 10.3390/s20061564.
For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.
对于多用户上行大规模多输入多输出（MIMO）系统，基于最小均方误差（MMSE）准则的线性信号检测算法在基站天线数量渐近大的条件下能实现近乎最优的性能。然而，当用户数量增大时，它在矩阵求逆方面涉及极高的复杂度。本文提出了一种基于改进的卡兹马尔兹方法的低复杂度软输出信号检测算法，该算法规避了矩阵求逆运算，从而将复杂度降低了一个数量级。同时，引入了一个最优松弛参数以进一步加快所提算法的收敛速度，并且还获得了两种用于信道解码的计算对数似然比（LLR）的近似方法。分析和仿真验证了所提算法优于各种典型的低复杂度信号检测算法。所提算法收敛迅速，仅需少量迭代就能实现其性能与MMSE算法相当接近。
